KEYNOTE TALKS - GMT(+9)
| Keynote talk 1 | Saturday 04.6.2022 | 14:50 - 15:40 | Room: 101 (Hybrid 1) |
| Bayesian estimation of multivariate stochastic volatility models using dynamic factors | |||
| Speaker: Y. Omori | Chair: Erricos Kontoghiorghes | ||
| Keynote talk 2 | Monday 06.6.2022 | 11:40 - 12:30 | Room: Main Theater (Hybrid 1) |
| An empirical evaluation of some long-horizon macroeconomic forecasts (virtual) | |||
| Speaker: K.D. West Co-authors: K. Lunsford | Chair: Masayuki Hirukawa | ||
| Keynote talk 3 | Monday 06.6.2022 | 17:05 - 17:55 | Room: Main Theater (Hybrid 1) |
| Multiple change-point detection for functional data (virtual) | |||
| Speaker: J.-M. Chiou | Chair: Ana Colubi | ||
PARALLEL SESSIONS - GMT(+9)
| Parallel session A: EcoSta2022 | Saturday 04.6.2022 | 08:25 - 09:40 |
| Session EV452 | Room: Virtual R12 |
| Contributions in methodological statistics and econometrics | Saturday 04.6.2022 08:25 - 09:40 |
| Chair: Ci-Ren Jiang | Organizer: EcoSta |
| Session EV465 | Room: Virtual R7 |
| Contributions in time series I | Saturday 04.6.2022 08:25 - 09:40 |
| Chair: Donggyu Kim | Organizer: EcoSta |
| E0431: W.W. Wei | |
| Spatial aggregation on high dimensional multivariate time series analysis | |
| E0567: T. McElroy, A. Roy | |
| A framework for time series aggregation and seasonality using marked point processes | |
| E1024: J. Goodridge, T. Brough | |
| Metallgesellschaft's hedging revisited: A superior predictive ability test analysis |
| Session EO165 | Room: 101 (Hybrid 1) |
| High-dimensional inference and reproducible learning | Saturday 04.6.2022 08:25 - 09:40 |
| Chair: Daoji Li | Organizer: Daoji Li |
| E0975: Y. Uematsu, K. Sawaya | |
| High-dimensional robust inference via the debiased rank lasso | |
| E1012: D. Li | |
| Reproducible learning for censored data via deep knockoffs | |
| E0776: K. Egashira, K. Yata, M. Aoshima | |
| Asymptotic behaviors of hierarchical clustering under high dimensional settings |
| Session EO351 | Room: 102 (Hybrid 2) |
| Change-point detection and variable selection for large-scale data | Saturday 04.6.2022 08:25 - 09:40 |
| Chair: Tao Zou | Organizer: Jun Li |
| E0251: S. Chakraborty, X. Zhang | |
| High-dimensional change-point detection using generalized homogeneity metrics | |
| E0772: X. Li, T. Zou, X. Liang | |
| Subbagging variable selection for massive data | |
| E0960: T.-L. Wu | |
| Cluster Detection Using Scan Statistics for High Dimensional Nonhomogeneous Poisson Process |
| Session EO357 | Room: 103 (Hybrid 3) |
| Analytical tools for biomedical data with complex structures | Saturday 04.6.2022 08:25 - 09:40 |
| Chair: Shuo Chen | Organizer: Shuo Chen |
| E0238: T. Ma | |
| High-dimension to high-dimension screening for detecting genome-wide epigenetic regulators of gene expression | |
| E0444: S. Simpson, M. Bahrami, C. Tomlinson, P. Laurienti | |
| Analytical tools for whole-brain networks: Fusing statistics and network science to understand brain function | |
| E0674: S. Chen | |
| The mediating role of neuroimaging data in age-related cognitive decline |
| Session EO413 | Room: 104 (Hybrid 4) |
| High-dimensional associations: Applications in spatial statistics (virtual) | Saturday 04.6.2022 08:25 - 09:40 |
| Chair: Yumou Qiu | Organizer: Yumou Qiu |
| E0980: Y. Qiu | |
| Inference for nonparanormal partial correlation via rank-based nodewise regression with applications to spatial data | |
| E0994: Y. Zhou, S. Pokal, Y. Guan, H. Wang, Y. Zhou | |
| An improved doubly robust estimator using partially recovered unmeasured spatial confounder | |
| E1017: B. Guo | |
| Testing and signal identification for two-sample high-dimensional covariances via multi-level thresholding |
| Session EO369 | Room: 105 (Hybrid 5) |
| Advances in statistical leaning theory and large-scale inference | Saturday 04.6.2022 08:25 - 09:40 |
| Chair: Peter Radchenko | Organizer: Peter Radchenko |
| E0637: G. Mukherjee, W. Sun, J. Luo | |
| Spatially adaptive false discovery rate thresholding for sparse estimation | |
| E0839: P. Radchenko | |
| Sparse high-dimensional regression with discrete optimization | |
| E0465: B. Rava | |
| A burden shared is a burden halved: A fairness-adjusted approach to classification |
| Session EO443 | Room: Virtual R1 |
| Advanced nonparametric and semiparametric methods | Saturday 04.6.2022 08:25 - 09:40 |
| Chair: Yuanyuan Guo | Organizer: Yuanyuan Guo |
| Session EO341 | Room: Virtual R10 |
| Recent advances with scalable and high-dimensional methods | Saturday 04.6.2022 08:25 - 09:40 |
| Chair: Sayar Karmakar | Organizer: Leo Duan |
| E0682: Y. Xu | |
| Bayesian sparse Gaussian mixture model in high dimensions | |
| E0676: S. Karmakar | |
| Long-term prediction for high-dimensional regression | |
| E0664: M. Shin, S. Wang, J. Liu | |
| Generative multiple-purpose sampler for weighted M-estimation |
| Session EO397 | Room: Virtual R11 |
| Recent developments in functional and time series data analysis | Saturday 04.6.2022 08:25 - 09:40 |
| Chair: Tianhao Wang | Organizer: Tianhao Wang |
| Session EO436 | Room: Virtual R2 |
| Nonparametric/ high dimensional methods: Neuroimaging and point clouds | Saturday 04.6.2022 08:25 - 09:40 |
| Chair: Luo Xiao | Organizer: Luo Xiao |
| E0552: C. Li, H. Zhang | |
| Tensor quantile regression with application to association between neuroimages and human intelligence | |
| E1006: J. Harezlak, T. Randolph, D. Brzyski, J. Goni, A. Steiner | |
| Incorporation of spatial- and connectivity-based cortical brain distances in regularized regression | |
| E1007: X. Li, S. Yu, Y. Wang, G. Wang, M.-J. Lai, L. Wang | |
| An efficient spline smoothing for 3D point cloud learning |
| Session EO333 | Room: Virtual R3 |
| Innovative weighting methods for causal inference | Saturday 04.6.2022 08:25 - 09:40 |
| Chair: Steve Yadlowsky | Organizer: Steve Yadlowsky |
| E0446: H. Namkoong | |
| Assessing external validity over worst-case subpopulations | |
| E0950: D. Hirshberg | |
| The basis for inference based on synthetic control methods | |
| E0440: E. Chung, M. Olivares | |
| Quantile-based test for heterogeneous treatment effects |
| Session EO111 | Room: Virtual R4 |
| Advances in statistical learning for complex data | Saturday 04.6.2022 08:25 - 09:40 |
| Chair: Wenbo Wu | Organizer: Wei Luo |
| Session EO159 | Room: Virtual R5 |
| L0-constrained statistical learning | Saturday 04.6.2022 08:25 - 09:40 |
| Chair: Ziwei Zhu | Organizer: Ziwei Zhu |
| E0883: Y. Guo, Z. Zhu, J. Fan | |
| Best subset selection is robust against design dependence | |
| E0899: S. Wu, Z. Zhu | |
| Sure early selection by searching for the best subset | |
| E0987: C. Wen | |
| Best subset selection in reduced rank regression |
| Session EO167 | Room: Virtual R6 |
| Environmental data science | Saturday 04.6.2022 08:25 - 09:40 |
| Chair: Soutir Bandyopadhyay | Organizer: Soutir Bandyopadhyay |
| E0610: C.Y. Lim | |
| Spatial regression with nonparametric modeling of Fourier coefficients | |
| E0611: S. Bandyopadhyay | |
| Advantages of model misspecification for block data | |
| E0688: S. Das, L. Zhang, G. Qian | |
| Periodogram regression, a semi-parametric mixed effects approach for modelling non-stationary tropical cyclone frequency |
| Session EO217 | Room: Virtual R8 |
| Recent advances in statistical methods for precision medicine | Saturday 04.6.2022 08:25 - 09:40 |
| Chair: Subharup Guha | Organizer: Yi Li |
| E1015: S. Guha, D. Christiani, Y. Li | |
| Unbiased multigroup comparisons by integrating multiple observational studies: A new concordant population approach | |
| E1020: K.Y. Wong, D. Zeng, D. Lin | |
| Semiparametric latent-class models for multivariate longitudinal and survival data | |
| E1026: S. DeSantis | |
| Propensity score matching and stratification for multiple and ordinal treatments: Application to an EHR-derived study |
| Session EO287 | Room: Virtual R9 |
| Advances in high-dimensional sampling methods | Saturday 04.6.2022 08:25 - 09:40 |
| Chair: Shiwei Lan | Organizer: Shiwei Lan |
| E0965: Y. Lu | |
| Sampling via birth-death dynamics | |
| E0726: S. Lan | |
| Scaling up Bayesian uncertainty quantification for inverse problems using deep neural networks | |
| E0770: A. Holbrook | |
| A quantum parallel Markov chain Monte Carlo |
| Parallel session B: EcoSta2022 | Saturday 04.6.2022 | 10:10 - 11:50 |
| Session EI007 | Room: 101 (Hybrid 1) |
| Innovations in functional data analysis (virtual) | Saturday 04.6.2022 10:10 - 11:50 |
| Chair: Fang Yao | Organizer: Xinyuan Song |
| Session EO141 | Room: 102 (Hybrid 2) |
| New methods for causal inference | Saturday 04.6.2022 10:10 - 11:50 |
| Chair: Luke Keele | Organizer: Luke Keele |
| E0239: A. Spieker, B. Shepherd, C. Birdrow | |
| Cumulative probability models and their utility in semi-parametric estimation of causal effects | |
| E0482: J. Roy | |
| Bayesian nonparametric methods for causal mediation analysis | |
| E0483: N. Mitra | |
| Estimating the causal effect of policy interventions in the presence of spillovers | |
| E0358: L. Keele | |
| Measuring racial disparities in emergency general surgery via approximate balancing weights |
| Session EO447 | Room: 103 (Hybrid 3) |
| Recent advances in inference for complex statistical models | Saturday 04.6.2022 10:10 - 11:50 |
| Chair: Jason Xu | Organizer: Jason Xu |
| Session EO115 | Room: 104 (Hybrid 4) |
| Methods for survival data analysis I | Saturday 04.6.2022 10:10 - 11:50 |
| Chair: Takeshi Emura | Organizer: Takeshi Emura |
| Session EO327 | Room: 105 (Hybrid 5) |
| Advances in statistical methods for observational studies (virtual) | Saturday 04.6.2022 10:10 - 11:50 |
| Chair: Rajarshi Mukherjee | Organizer: Rajarshi Mukherjee |
| E0464: K. Basu | |
| Personalized treatment selection using causal heterogeneity | |
| E0469: L. Liu | |
| A splitting Hamiltonian Monte Carlo method for efficient sampling | |
| E0759: N. Laha, A. Sonabend, R. Mukherjee, T. Cai | |
| Optimal dynamic treatment regimes via smooth surrogate losses | |
| E0854: R. Dey | |
| Efficient and accurate genome-wide survival association analysis controlling for sample relatedness in biobanks |
| Session EO421 | Room: 106 (Hybrid 6) |
| Recent advances in quantile regression methods (virtual) | Saturday 04.6.2022 10:10 - 11:50 |
| Chair: Jeong Hoon Jang | Organizer: Jeong Hoon Jang |
| E0284: C. Yu, H. Li, G. Ma | |
| Cross-sectional analysis of conditional stock returns: quantile regression with machine learning | |
| E0339: W. Ling, W. Zhang, B. Cheng, Y. Wei | |
| Zero-inflated quantile rank-score based test with application to scRNA-seq differential gene expression analysis | |
| E0466: B. Wei, L. Peng, Z. Mei-Jie, J. Fine | |
| Estimation of causal quantile effects with a binary instrumental variable and censored data | |
| E0918: J.H. Jang | |
| Function-on-function quantile regression model for predicting glucose levels and excursions |
| Session EO273 | Room: 107 (Hybrid 7) |
| Recent advances in latent variable analysis and psychometrics | Saturday 04.6.2022 10:10 - 11:50 |
| Chair: Gongjun Xu | Organizer: Gongjun Xu |
| Session EO035 | Room: Virtual R1 |
| Financial big data modeling | Saturday 04.6.2022 10:10 - 11:50 |
| Chair: Donggyu Kim | Organizer: Donggyu Kim |
| E0218: D. Kim, M. Shin | |
| High-dimensional high-frequency regression | |
| E0455: S.H. Choi, D. Kim | |
| Large volatility matrix analysis using global and national factor models | |
| E0241: M. Shin, D. Kim, Y. Wang, J. Fan | |
| Factor and idiosyncratic VAR-Ito volatility models for heavy-tailed high-frequency financial data | |
| E0253: M. Oh, D. Kim | |
| Effect of the U.S.-China trade war on stock markets: A financial contagion perspective |
| Session EO037 | Room: Virtual R10 |
| Modern statistics for causality analysis and high-dimensional inference | Saturday 04.6.2022 10:10 - 11:50 |
| Chair: Shujie Ma | Organizer: Shujie Ma |
| E0245: Z. Zhang, Z. Hu, D. Follmann, L. Nie | |
| Estimating the average treatment effect in randomized clinical trials with all-or-none compliance | |
| E0247: H. Cai, Y. Shen, R. Song | |
| Doubly robust interval estimation for optimal policy evaluation in online learning | |
| E0257: J. Zhao | |
| Statistical exploitation of unlabeled data under high dimensionality | |
| E0406: Y. Zhu | |
| High-dimensional causal mediation analysis |
| Session EO247 | Room: Virtual R11 |
| Recent advances in biomedical and EHR data analysis | Saturday 04.6.2022 10:10 - 11:50 |
| Chair: Wenlin Dai | Organizer: Wenlin Dai |
| E0779: X. Luo, Q. Wu | |
| Estimating heterogeneous gene regulatory networks from zero-inflated single-cell expression data | |
| E0782: H. Zhou | |
| A modern theory for high-dimensional Cox regression models | |
| E0875: K. He, R.K.W. Wong, Y. Zhou, F. Zhang | |
| Multivariate varying-coefficient models via tensor decomposition | |
| E1014: H. Wu | |
| Use of electronic health records data for research: Challenges and opportunities |
| Session EO445 | Room: Virtual R12 |
| Recent advances in reliability and counting processes | Saturday 04.6.2022 10:10 - 11:50 |
| Chair: Tony Sit | Organizer: Tony Sit |
| E0246: T. Sit | |
| Distributed censored quantile regression | |
| E0249: M.H. Ling | |
| Likelihood inference for one-shot device testing under frailty models | |
| E1013: C.W. Chu, T. Sit, Z. Ying | |
| Censored quantile regression with time-dependent covariates | |
| E1021: P.S.B. Chan | |
| On the computation of system signature |
| Session EO095 | Room: Virtual R13 |
| Learning from complex data: New directions and innovations | Saturday 04.6.2022 10:10 - 11:50 |
| Chair: Shan Yu | Organizer: Guannan Wang |
| E0822: S. Yu, A. Kusmec, L. Wang, D. Nettleton | |
| Fusion learning of functional linear regression with application to genotype-by-environment interaction studies | |
| E0853: L. Wang, Y. Wang, G. Wang | |
| Statistical inference for mean functions of 3D functional objects | |
| E0878: M. Tadesse | |
| Variable selection in mixture models via stochastic partitioning | |
| E0952: L. Kong | |
| A Gaussian copula function-on-scalar regression in reproducing kernel Hilbert spaces |
| Session EO099 | Room: Virtual R2 |
| Advances in Bayesian methodology and computation | Saturday 04.6.2022 10:10 - 11:50 |
| Chair: James Flegal | Organizer: James Flegal |
| E0544: D. Vats, M. Agarwal | |
| Globally-centered autocovariances in MCMC | |
| E0551: Z. Li | |
| Bayesian latent class model for multi-source domain adaptation | |
| E0754: J. Flegal, D. Vats | |
| Lugsail lag windows for estimating time-average covariance matrices | |
| E0943: A. King | |
| Semiparametric Bayesian discrete event time modeling |
| Session EO209 | Room: Virtual R3 |
| Recent advances on statistical modeling of complex data | Saturday 04.6.2022 10:10 - 11:50 |
| Chair: Youngdeok Hwang | Organizer: Xinwei Deng |
| E0966: B.-J. Kim, I. Kim | |
| Joint semiparametric kernel machine network regression | |
| E0976: S. Kim | |
| Time delay estimation of traffic congestion based on statistical causality | |
| E0938: Y. Hwang | |
| Bayesian model calibration and sensitivity analysis for oscillating biological experiments | |
| E0591: K. Zhu, H. Liu, Y. Yang | |
| Blocking, rerandomization, and regression adjustment in randomized experiments with high-dimensional covariates |
| Session EO223 | Room: Virtual R4 |
| Recent advances in financial time series | Saturday 04.6.2022 10:10 - 11:50 |
| Chair: Cathy W-S Chen | Organizer: Cathy W-S Chen |
| E0242: L.-H. Sun | |
| Online change point detection via copula based Markov models | |
| E0269: S.-F. Huang, H.-H. Chiang, Y.-J. Lin | |
| A network autoregressive model with GARCH effects and its applications | |
| E0310: H.-W. Teng, W.K. Haerdle | |
| Pricing and hedging crypto options | |
| E0489: E.M.-H. Lin | |
| A Bayesian analysis in long- and short-term financial volatility components with mixture distributions |
| Session EO359 | Room: Virtual R5 |
| Tensor and multilayer networks | Saturday 04.6.2022 10:10 - 11:50 |
| Chair: Ivor Cribben | Organizer: Ivor Cribben |
| E0579: M. Yuan, Z. Shang | |
| Statistical limits for testing the correlation of hypergraphs | |
| E0725: Y. Yuan | |
| Community detection with dependent connectivity | |
| E0817: W. Zhang, I. Cribben, S. Petrone, M. Guindani | |
| Bayesian time-varying tensor vector autoregressive models for dynamic effective connectivity | |
| E0959: D. Ofori-Boateng | |
| Time series of weakly dependent tensors |
| Session EO283 | Room: Virtual R6 |
| Recent development in complex data analysis | Saturday 04.6.2022 10:10 - 11:50 |
| Chair: Yanlin Tang | Organizer: Yanlin Tang |
| Session EO313 | Room: Virtual R7 |
| Nonparametric and semiparametric statistics | Saturday 04.6.2022 10:10 - 11:50 |
| Chair: Yoshihiko Nishiyama | Organizer: Yoshihiko Nishiyama |
| E0433: M. Iwasawa, Y. Nishiyama, K. Hitomi | |
| Optimal minimax rates of specification testing with data-driven bandwidth | |
| E0439: Y. Maesono, S. Penev | |
| Improved confidence intervals for expectiles in risk management | |
| E0429: Y. Kakizawa | |
| Asymmetric kernel density estimation for biased data | |
| E0425: Y. Nishiyama, S. Imai | |
| Higher-order asymptotic properties of the kernel density estimator with plug-in bandwidth |
| Session EO319 | Room: Virtual R8 |
| Recent advances in Bayesian data analysis | Saturday 04.6.2022 10:10 - 11:50 |
| Chair: Weixuan Zhu | Organizer: Weixuan Zhu |
| E0566: Y. Ni | |
| Ordinal causal discovery | |
| E0585: S. Wang | |
| Bayesian parameter inference and model selection for differential equation models | |
| E0511: K.-D. Dang, L. Ryan, R. Cook, T. Akkaya-Hocagil, S. Jacobson, J. Jacobson | |
| Bayesian outcome selection modelling | |
| E1030: W. Zhu | |
| Covariate dependent Beta-GOS process |
| Session EO335 | Room: Virtual R9 |
| Design and analysis of experiments | Saturday 04.6.2022 10:10 - 11:50 |
| Chair: Boxin Tang | Organizer: Boxin Tang |
| E0200: J. Zhou | |
| Computing multiple-objective optimal regression designs via CVX | |
| E0337: Y. He, G. Chen | |
| Linear orthogonal arrays of strength three and their applications | |
| E0476: G. Chen, B. Tang | |
| A study of orthogonal array-based designs under a broad class of space-filling criteria | |
| E1018: M.-Q. Liu | |
| Column-orthogonal strong orthogonal arrays |
| Parallel session C: EcoSta2022 | Saturday 04.6.2022 | 13:00 - 14:40 |
| Session EI009 | Room: 101 (Hybrid 1) |
| Recent advances in Bayesian econometrics and statistics (virtual) | Saturday 04.6.2022 13:00 - 14:40 |
| Chair: Toshiaki Watanabe | Organizer: Toshiaki Watanabe |
| E0153: M. So | |
| Bayesian analysis of multiple networks for financial risk management | |
| E0154: C.W.-S. Chen, K.Y.-K. Wang | |
| On the quantile market risk factor model with heteroskedasticity, skewness, and leptokurtosis | |
| E0684: J. Nakajima | |
| Measuring regional economic uncertainty |
| Session EO183 | Room: 102 (Hybrid 2) |
| Empirical covariance operators and beyond | Saturday 04.6.2022 13:00 - 14:40 |
| Chair: Moritz Jirak | Organizer: Moritz Jirak |
| E0308: M. Lopes, B. Erichson, M. Mahoney | |
| Bootstrapping the operator norm in high dimensions: Error estimation for covariance matrices and sketching | |
| E0603: X. Ding | |
| Optimal and adaptive invariant shrinkage estimators for general large covariance and precision matrices | |
| E0813: M. Wahl, M. Jirak | |
| Quantitative limit theorems and bootstrap approximations for empirical spectral projectors | |
| E0941: N. Parolya, J. Heiny, D. Kurowicka | |
| Logarithmic law for large sample correlation matrices |
| Session EO325 | Room: 103 (Hybrid 3) |
| Data science in social science | Saturday 04.6.2022 13:00 - 14:40 |
| Chair: Yasumasa Matsuda | Organizer: Yasumasa Matsuda |
| E0350: T. Ishihara | |
| Panel data quantile regression for treatment effect models | |
| E0460: M. Yuda, F. Chen, M. Wakabayashi | |
| Health transition after retirement: Empirical evidence from public pension reform in Japan | |
| E0602: Y. Matsuda | |
| Convolutional regression for big spatial data | |
| E0926: S.I.-M. Ko | |
| Indian buffet process factor model for counterfactual analysis |
| Session EO113 | Room: 104 (Hybrid 4) |
| Regime switching and change dynamics | Saturday 04.6.2022 13:00 - 14:40 |
| Chair: Matus Maciak | Organizer: Matus Maciak |
| E0479: M. Pesta, M. Maciak, O. Okhrin | |
| Infinitely stochastic micro forecasting | |
| E0480: M. Maciak, M. Pesta, G. Ciuperca | |
| Real-time changepoint detection in a nonlinear expectile model | |
| E0550: O. Okhrin, N. Gillmann | |
| Economic policy uncertainty with ada-net | |
| E0834: I. Mizera | |
| Nonparametric maximum likelihood and related methods in infinite-dimensional situations: Convex optimization aspects |
| Session EO423 | Room: 105 (Hybrid 5) |
| Joint modeling of complex dependent data | Saturday 04.6.2022 13:00 - 14:40 |
| Chair: Xinyuan Song | Organizer: Xinyuan Song |
| E0348: T. Emura, V. Rondeau, S. Casimir | |
| Conditional copula models for correlated survival endpoints in individual patient data meta-analysis | |
| E0504: R. Sun, X. Song | |
| A tree-based Bayesian accelerated failure time cure model for estimating heterogeneous treatment effect | |
| E0505: Y. Lin, Q. Fan, X. Song | |
| Robust joint estimation of treatment effect via possible dependent instrumental variables | |
| E0647: J. Pan, L. Zhang | |
| Bayesian adaptive lasso factor analysis models with pre- and post-test binary data |
| Session EO285 | Room: 106 (Hybrid 6) |
| Advances in analysis of complex dependent data | Saturday 04.6.2022 13:00 - 14:40 |
| Chair: Takashi Owada | Organizer: Shuyang Bai |
| E0618: T. Owada | |
| Large deviation principle for geometric and topological functionals and associated point processes | |
| E0752: F. Fang, A. Belloni, A. Volfovsky | |
| Adaptive estimators for causal effects under network interference | |
| E0930: A. Betken | |
| Testing for the independence of long-range dependent time series based on distance correlation | |
| E0964: T. Zhang | |
| High quantile regression for tail dependent time series |
| Session EO235 | Room: 107 (Hybrid 7) |
| Bayesian methods and their applications | Saturday 04.6.2022 13:00 - 14:40 |
| Chair: Kuo-Jung Lee | Organizer: Kuo-Jung Lee, Ray-Bing Chen |
| E0626: K. Irie, A. Tevfik, C. Glynn | |
| Sequential forecasting for bursty count data | |
| E0692: H. Kang, I. Lyu, K. Albert, B. Boyd, B. Landman, W. Taylor | |
| A comparison of whole brain connectivity between depressed and non-depressed using a Bayesian spatio-temporal model | |
| E0774: W.-T. Lai | |
| Variational Bayesian inference for network autoregression models |
| Session EO039 | Room: Virtual R1 |
| Modeling tail events | Saturday 04.6.2022 13:00 - 14:40 |
| Chair: Abdelaati Daouia | Organizer: Abdelaati Daouia |
| E0787: A. Usseglio-Carleve, G. Stupfler | |
| Composite bias-reduced Lp-quantile-based estimators of extreme quantiles and expectiles | |
| E0624: G. Stupfler, A. Daouia, S. Padoan | |
| Optimal pooling and distributed inference for the tail index and extreme quantiles | |
| E0328: M. Allouche, S. Girard, E. Gobet | |
| EV-GAN: Simulation of extreme events with ReLU neural networks | |
| E0458: C. Adam, I. Gijbels | |
| Conditional expectile-based risk measures |
| Session EO117 | Room: Virtual R2 |
| Statistical network data analysis | Saturday 04.6.2022 13:00 - 14:40 |
| Chair: Binyan Jiang | Organizer: Binyan Jiang |
| Session EO185 | Room: Virtual R3 |
| On the second-order dynamics of intricate functional data | Saturday 04.6.2022 13:00 - 14:40 |
| Chair: Alessia Caponera | Organizer: Alessia Caponera |
| E0296: T. Hsing, S. Stoev, R. Kartsioukas | |
| Spectral density estimation of function-valued spatial processes | |
| E0969: A. van Delft, H. Dette | |
| Pivotal tests for relevant differences in the second order dynamics of functional time series | |
| E0265: S. Tavakoli, M. Hallin, G. Nisol | |
| Factor models for high-dimensional functional time series | |
| E0780: N. Mohammadi Jouzdani, L. Santoro, V. Panaretos | |
| Nonparametric statistical inference for i.i.d. sparsely observed diffusions: An FDA perspective |
| Session EO151 | Room: Virtual R4 |
| Non-linear dependence in multivariate time series | Saturday 04.6.2022 13:00 - 14:40 |
| Chair: Hernando Ombao | Organizer: Hernando Ombao |
| E0236: A. Shojaie | |
| Estimation and inference for networks of multi-experiment point processes | |
| E0563: M.K. Chung, H. Ombao, S. Dakurah | |
| Dynamic topological data analysis on time varying trees and cycles | |
| E0617: J. Goldsmith, A. Garcia de la Garza, B. Sauerbrei, A. Hantman | |
| Adaptive functional principal component analysis | |
| E0998: R. Huser, M. Guerrero, H. Ombao | |
| Conex-connect: Learning patterns in extremal brain connectivity from multi-channel EEG data |
| Session EO375 | Room: Virtual R5 |
| Recent advances on actuarial theory and statistics | Saturday 04.6.2022 13:00 - 14:40 |
| Chair: Yiying Zhang | Organizer: Yiying Zhang |
| E0634: Y. Zhang | |
| Distortion risk contribution ratio measures: Definitions and comparisons | |
| E0704: G. Gao | |
| Double boosting of mean and dispersion in Tweedie's compound Poisson model with pre-defined base learners | |
| E0711: Y. Yong, Y. Zhang | |
| Credibility theory for mean-variance premium principles | |
| E0800: Y. Wang | |
| Optimal reinsurance for multivariate risks |
| Session EO029 | Room: Virtual R6 |
| Spatial data modeling: Theory and applications | Saturday 04.6.2022 13:00 - 14:40 |
| Chair: Pavel Krupskiy | Organizer: Pavel Krupskiy |
| E0371: T. Chu | |
| Mixed domain asymptotics for geostatistical processes | |
| E0484: G. Qian, A. Tordesillas, H. Zheng | |
| Landslide forecast by time series modelling and analytics of high-dimensional and non-stationary ground motion data | |
| E0557: S. Mondal, S. Abdulah, H. Ltaief, Y. Sun, M. Genton, D. Keyes | |
| Parallel approximations of the Tukey g-and-h likelihoods and predictions for non-Gaussian geostatistics | |
| E0731: B. Nasri | |
| Spatio-temporal Markov regime-switching models based on copulas |
| Session EO181 | Room: Virtual R7 |
| Recent advances in time series econometrics | Saturday 04.6.2022 13:00 - 14:40 |
| Chair: Jihyun Kim | Organizer: Jihyun Kim |
| E0196: N. Salish, S. Otto | |
| Dynamic factor model for functional time series: Identification, estimation, and prediction | |
| E0289: A. Bykhovskaya, V. Gorin | |
| Cointegration in large VARs | |
| E0438: M. Yamashita | |
| Option-implied forecasts with robust change of measure | |
| E0473: B. Hu | |
| Asymptotics of functional principal component analysis with weakly dependent data |
| Session EO269 | Room: Virtual R8 |
| Recent advances in time series analysis | Saturday 04.6.2022 13:00 - 14:40 |
| Chair: Kaiji Motegi | Organizer: Kaiji Motegi |
| E0695: K. Zhu | |
| Multifrequency-band tests for white noise under heteroscedasticity | |
| E0913: D. Nagakura, T. Watanabe | |
| State-space method for the quadratic estimator of integrated variance in the presence of market microstructure noise | |
| E0186: Y. Iitsuka, K. Motegi | |
| Regional interdependence of the Japan REIT market: A heteroscedasticity-robust time series approach | |
| E0183: K. Motegi, J. Dennis, S. Hamori | |
| Conditional threshold autoregression (CoTAR) |
| Session EO257 | Room: Virtual R9 |
| Estimation for semi-parametric mixture model | Saturday 04.6.2022 13:00 - 14:40 |
| Chair: Marie du Roy de Chaumaray | Organizer: Marie du Roy de Chaumaray |
| E0475: K. Shimotsu, H. Kasahara | |
| Testing the order of multivariate normal mixture models | |
| E0193: M. Marbac, M. du Roy de Chaumaray | |
| Full model estimation for non-parametric multivariate finite mixture models | |
| E0301: G. Chagny, A. Channarond, V.H. Hoang, A. Roche | |
| Adaptive estimation of the nonparametric component under a two-class mixture model | |
| E0180: W. Yao | |
| Semiparametric mixture of regression with unspecied error distributions |
| Parallel session E: EcoSta2022 | Saturday 04.6.2022 | 16:10 - 18:15 |
| Session EV453 | Room: Virtual R5 |
| Contributions in methodological econometrics | Saturday 04.6.2022 16:10 - 18:15 |
| Chair: Wai-keung Li | Organizer: EcoSta |
| E0794: G. Liu-Evans, G. Phillips | |
| The bias of the modified limited information maximum likelihood estimator in static simultaneous equation models | |
| E0799: A. Quaini, F. Trojani | |
| Proximal estimation and inference | |
| E0434: I. Paraskevopoulos | |
| The role of history in measurement | |
| E1038: Z. Huang, C. Wang, J. Yao | |
| Detecting many weak instruments |
| Session EI005 | Room: 101 (Hybrid 1) |
| Recent developments in econometric time series | Saturday 04.6.2022 16:10 - 18:15 |
| Chair: Masayuki Hirukawa | Organizer: Masayuki Hirukawa |
| E0157: T. Yamagata, K. Hayakawa, G. Cui, S. Nagata | |
| A robust approach to slope heterogeneity in linear models with interactive effects for large panel data | |
| E0158: A. Prokhorov, R. James, H. Leung | |
| A machine learning attack on illegal trading | |
| E1041: M. Shintani, T. Kurita | |
| Johansen test with Fourier-type smooth non-linear trends in cointegrating relations |
| Session EO137 | Room: 102 (Hybrid 2) |
| Finance and macroeconometrics | Saturday 04.6.2022 16:10 - 18:15 |
| Chair: Etsuro Shioji | Organizer: Etsuro Shioji |
| E0452: T. Matsuki | |
| Revisiting output convergence and economic growth determinants in OECD and some emerging countries | |
| E0424: S.H. Lee, K.H. Kang | |
| Term premiums and regime-switching prices of macro risks | |
| E0233: Y. Yoshida, Y. Sasaki, S. Zhang, W. Zhai | |
| Exchange rate pass-through under the unconventional monetary policy regime | |
| E0216: K.H. Kang, K. Kim | |
| When aggregate stock returns are negatively-skewed: International evidence | |
| E0300: E. Shioji | |
| The pandemic and government bonds: Evidence from volatility smiles in Japan |
| Session EO225 | Room: 103 (Hybrid 3) |
| Recent advances in survival analysis | Saturday 04.6.2022 16:10 - 18:15 |
| Chair: Byungtae Seo | Organizer: Sangwook Kang |
| E0342: T.-S. Lu | |
| Semiparametric accelerated failure time model with interval-censored data under outcome-dependent sampling design | |
| E0584: S. Kim, S. Kang | |
| Quantile residual life regression analysis of HIV/AIDS patients in Korea | |
| E0653: K. Beppu, K. Morikawa, J. Im | |
| Imputation with verifiable identification condition for nonignorable missing outcomes | |
| E0775: B. Seo, S. Kang | |
| Accelerated failure time modelling via nonparametric mixtures | |
| E0906: J. Im, T. Park, S. Kang | |
| Fractional imputation approach for Cox regression with missing covariate |
| Session EO271 | Room: 104 (Hybrid 4) |
| Learning and modelling of complex time series and spatial processes | Saturday 04.6.2022 16:10 - 18:15 |
| Chair: Zudi Lu | Organizer: Zudi Lu |
| E0423: A. Gupta, M.H. Seo | |
| Robust inference on infinite and growing dimensional time series regression | |
| E0485: T. Kihara | |
| Nonparametric maximum likelihood estimation for GINAR(p) models | |
| E0582: F. Akashi, J. Hirukawa, K. Fokianos | |
| Weighted estimation procedures for time-varying heavy-tailed processes | |
| E0632: L. Wang, Z. Lu | |
| Adaptive group fused Lasso for panel threshold model with cross-sectional dependence | |
| E0884: Z. Lu, X. Ren, R. Zhang | |
| On dynamic functional-coefficient autoregressive spatio-temporal models with irregular location wide nonstationarity |
| Session EO377 | Room: 105 (Hybrid 5) |
| Data analytics in statistics and econometrics | Saturday 04.6.2022 16:10 - 18:15 |
| Chair: Cy Sin | Organizer: Cy Sin |
| E0258: H.-L. Hsu | |
| A greedy active learning algorithm in multinomial logistic regression | |
| E0299: H.H. Kwok | |
| Shrinkage estimations for social interactions models | |
| E0791: J.-H. Su | |
| No-regret forecasting with egalitarian committees | |
| E0857: S.-Y. Yin | |
| Regularized estimation in dynamic panel with a multifactor error structure | |
| E0911: W.-Y. Wu | |
| Parameter estimation in a biomechanical model with multiplicative errors |
| Session EO391 | Room: 107 (Hybrid 7) |
| Recent advances in shrinkage estimation | Saturday 04.6.2022 16:10 - 18:15 |
| Chair: Yuzo Maruyama | Organizer: Yuzo Maruyama |
| E0338: Y. Hamura | |
| Bayesian shrinkage estimation for stratified count data | |
| E0524: C.-H. Yang, H. Doss, B. Vemuri | |
| An empirical Bayes approach to shrinkage estimation on the manifold of symmetric positive-definite matrices | |
| E0717: T. Matsuda | |
| Adapting to arbitrary quadratic loss via singular value shrinkage | |
| E0841: R. Yuasa, T. Kubokawa | |
| Weighted shrinkage estimators of normal mean matrices | |
| E0742: M. Okudo, F. Komaki | |
| Bayes extended estimators with shrinkage priors for multivariate normal models |
| Session EO215 | Room: Virtual R1 |
| Bayesian computation for complex models | Saturday 04.6.2022 16:10 - 18:15 |
| Chair: David Nott | Organizer: David Nott |
| E0164: S.L.L. Tan | |
| Efficient data augmentation techniques for state space models | |
| E0240: D. Nott, X. Yu, M.S. Smith | |
| Variational inference for cutting feedback with misspecified models | |
| E0252: M. Smith, R. Loaiza-Maya, D. Nott, P. Danaher | |
| Fast and accurate variational inference for models with many latent variables | |
| E0448: C. Drovandi, B. Lawson, A. Browning, A. Jenner | |
| Population calibration using likelihood-free Bayesian inference | |
| E0847: R. Kohn, D. Nott, D. Gunawan | |
| Flexible variational Bayes based on a copula of a mixture of normals |
| Session EO438 | Room: Virtual R2 |
| Recent advances in Machine Learning | Saturday 04.6.2022 16:10 - 18:15 |
| Chair: Bharath Sriperumbudur | Organizer: Bharath Sriperumbudur |
| E0316: Z. Szabo, P.-C. Aubin-Frankowski | |
| When shape constraints meet kernel machines | |
| E0317: K. Balasubramanian | |
| Fractal Gaussian networks: A sparse random graph model based on Gaussian multiplicative chaos | |
| E0318: Y. Mroueh | |
| Measuring generalization with optimal transport | |
| E0314: M. Arbel | |
| Annealed flow transport Monte Carlo | |
| E0545: K. Muandet | |
| Modern kernel methods for econometrics |
| Session EO169 | Room: Virtual R3 |
| Extreme value analysis in time and space | Saturday 04.6.2022 16:10 - 18:15 |
| Chair: Gilles Stupfler | Organizer: Gilles Stupfler |
| E0477: M. Oesting | |
| Long range dependence in the tails | |
| E0636: A. Daouia, T. Laurent, G. Stupfler | |
| Heavy-tailed extremile regression in risky seismic areas | |
| E0675: R. Kulik | |
| Asymptotic expansions for blocks estimators of cluster indices | |
| E0798: S. Padoan, G. Stupfler, A. Davison | |
| Tail risk inference via expectiles in heavy-tailed time series |
| Session EO189 | Room: Virtual R4 |
| Bayesian methods in economics | Saturday 04.6.2022 16:10 - 18:15 |
| Chair: Veronica Ballerini | Organizer: Veronica Ballerini |
| E0605: F. DAmario, M. Ciganovic | |
| Forecasting cryptocurrencies log-returns: A Bayesian approach using social media sentiment indexes | |
| E0651: G. Grossi, M. Mariani, A. Mattei, F. Mealli | |
| Bayesian principal stratification with longitudinal data and truncation by death | |
| E0667: S. Noirjean, M. Biggeri, L. Forastiere, F. Mealli, M. Nannini | |
| Estimating causal effects of community health financing via principal stratification | |
| E0858: R. Barone, V. Ballerini, B. Liseo | |
| Modelling preferences via Wallenius process |
| Session EO329 | Room: Virtual R7 |
| Statistics to improve the development of cultivars | Saturday 04.6.2022 16:10 - 18:15 |
| Chair: Reka Howard | Organizer: Hiroyoshi Iwata, Reka Howard, Bertrand Clarke |
| E0837: K. Hamazaki, H. Iwata | |
| Future-oriented strategy via simulations optimizes breeding schemes with selection indices | |
| E0840: M. Delattre, H. Iwata, J. Tressou | |
| Modelling soybean growth: A nonlinear mixed model approach | |
| E0873: G. Morota | |
| Genome-enabled analysis of time-series high-throughput phenotyping data | |
| E0891: A. Onogi | |
| Prediction of flowering and maturity time of soybean using stacking | |
| E0803: R. Howard, V. Manthena, D. Jarquin | |
| Sparse classification with multi-type data |
| Session EO251 | Room: Virtual R8 |
| Advanced statistical methods in economics and finance | Saturday 04.6.2022 16:10 - 18:15 |
| Chair: Huei-Wen Teng | Organizer: Huei-Wen Teng |
| E0291: Y.-C. Hsu | |
| Testing monotonicity of mean potential outcomes in a continuous treatment | |
| E0305: Y.-M. Yen | |
| Estimations of the conditional tail average treatment effect | |
| E0923: Y.-Y. Tzeng | |
| Monte Carlo simulation and its applications | |
| E0972: W.-C. Miao, X.C.-S. Lin, H.Y.-J. Chien | |
| Analysis of value-at-risk and expected shortfall under a jump-diffusion model with left-skewed jump sizes | |
| E1009: M.-K. Chen, M.-E. Wu, W.-S. Wu | |
| Quantitative trading of vertical spread option strategies with stop-loss by machine learning |
| Session EO395 | Room: Virtual R9 |
| Statistics on shapes and manifolds | Saturday 04.6.2022 16:10 - 18:15 |
| Chair: Joern Schulz | Organizer: Joern Schulz |
| E0221: S. Sommer | |
| Stochastic shape analysis and probabilistic geometric statistics | |
| E0347: E. Grong, S. Sommer | |
| Most probable paths for anisotropic Brownian motions on manifolds | |
| E0627: M. Taheri Shalmani, J. Schulz | |
| Statistical analysis of locally parameterized shapes | |
| E0697: Z. Liu | |
| Geometric and statistical models of analyzing two-object complexes |
| Session EC428 | Room: 106 (Hybrid 6) |
| Contributions in financial econometrics (in-person) | Saturday 04.6.2022 16:10 - 18:15 |
| Chair: Yuta Koike | Organizer: EcoSta |
| E0722: S. Hediger, J. Naef | |
| Shrinking in COMFORT | |
| E0786: K. Chen, H.Y. Wong | |
| Duality in optimal consumption-investment problems with alternative data | |
| E0970: W. Chen, Y. Jiang, R. Gerlach | |
| On the construction of neural networks for value-at-risk forecasting | |
| E0948: C.Y. Li, A. Shkolnik | |
| Factor analysis for heavy-tailed, heteroscedastic data | |
| E0671: J. Magnus | |
| On the uncertainty of a combined forecast: The critical role of correlation |
| Parallel session F: EcoSta2022 | Sunday 05.6.2022 | 08:00 - 10:05 |
| Session EO417 | Room: 101 (Hybrid 1) |
| Statistical applications in neuroscience | Sunday 05.6.2022 08:00 - 10:05 |
| Chair: Elizabeth Sweeney | Organizer: Elizabeth Sweeney |
| E0343: K. Linn, R. Shinohara, J. Beer | |
| Longitudinal ComBat: A method for harmonizing longitudinal multi-scanner imaging data | |
| E0758: E. Sweeney | |
| Quantitative susceptibility maps in multiple sclerosis lesions | |
| E0880: J. Wrobel | |
| Modeling trajectories using functional linear first-order differential equations | |
| E1019: T. Ogden, B. Shi | |
| Nonparametric functional data modeling of pharmacokinetic processes with applications in dynamic PET imaging |
| Session EO015 | Room: 102 (Hybrid 2) |
| Recent developments on network and tensor data analysis | Sunday 05.6.2022 08:00 - 10:05 |
| Chair: Yuan Zhang | Organizer: Yuan Zhang |
| E0292: C. Lam | |
| Rank and factor loadings estimation in time series tensor factor model by pre-averaging | |
| E0219: Y. Zhen, J. Wang | |
| Community detection in general hypergraph via garph embedding | |
| E0332: C. Lee, M. Wang | |
| Smooth tensor estimation with unknown permutations | |
| E0597: D. Choi | |
| Randomization inference in experiments on networks | |
| E0831: X. Han | |
| Individual-centered partial information in social networks |
| Session EO045 | Room: 103 (Hybrid 3) |
| Precision medicine with complex data (virtual) | Sunday 05.6.2022 08:00 - 10:05 |
| Chair: Yifan Cui | Organizer: Zeyu Bian, Yifan Cui |
| E0889: C. Shi | |
| A reinforcement learning framework for A/B testing | |
| E0951: Z. Bian, E. Moodie, S. Bhatnagar | |
| Variable selection for individualized treatment rules with discrete outcomes | |
| E0904: Y. Wu, L. Wang, H. Fu | |
| Model-assisted uniformly honest inference for optimal treatment regimes in high dimension | |
| E0900: M. Li, C. Shi, Z. Wu, P. Fryzlewicz | |
| Reinforcement learning in possibly nonstationary environments | |
| E0898: Y. Zhang, J. Bradic, W. Ji | |
| Dynamic treatment effects: High-dimensional inference under model misspecification |
| Session EO097 | Room: 104 (Hybrid 4) |
| New frontiers in network data analysis | Sunday 05.6.2022 08:00 - 10:05 |
| Chair: Emma Jingfei Zhang | Organizer: Emma Jingfei Zhang |
| E0462: E.J. Zhang | |
| Using maximum entry-wise deviation to test the goodness-of-fit for stochastic block models | |
| E0499: J. Stewart | |
| Learning cross-layer dependence structure for multilayer networks | |
| E0751: S. Paul | |
| Modeling continuous-time networks of relational events | |
| E1008: S. Sengupta, M. Pensky, S. Bhadra | |
| Scalable community detection in massive networks via predictive inference | |
| E0957: N. Egami | |
| Identification and estimation of causal peer effects using double negative controls for unmeasured network confounding |
| Session EO195 | Room: 105 (Hybrid 5) |
| Semi-parametric inference and modeling with shape-constraints (virtual) | Sunday 05.6.2022 08:00 - 10:05 |
| Chair: Hyebin Song | Organizer: Hyebin Song |
| E0815: Y.E. Shin | |
| Joint estimation of monotone curves via functional principal component analysis | |
| E0823: T. Westling, Y. Wu | |
| Nonparametric inference under a monotone hazard ratio order | |
| E0835: Y. Miyatake, T. Matsuda | |
| Piecewise monotone estimation in one-parameter exponential families | |
| E0907: S. Acharyya, D. Pati, D. Bandyopadhyay | |
| A monotone single index model for missing-at-random longitudinal proportion data |
| Session EO049 | Room: 106 (Hybrid 6) |
| Adaptive clinical trial design | Sunday 05.6.2022 08:00 - 10:05 |
| Chair: Yisheng Li | Organizer: Yisheng Li |
| E0896: H. Pan | |
| Platform designs with added new arms | |
| E0932: Y. Li | |
| A semi-mechanistic dose-finding design in oncology using pharmacokinetic/pharmacodynamic modeling | |
| E0954: Y. Li | |
| A Bayesian adaptive design for pediatric basket trials | |
| E1004: A. Nakakura, S. Morita, Y. Sugitani, H. Yamamoto | |
| Biomarker-based Bayesian randomized clinical trial design for identifying a target population |
| Session EO109 | Room: 107 (Hybrid 7) |
| Causal inference and reinforcement learning (virtual) | Sunday 05.6.2022 08:00 - 10:05 |
| Chair: Peter Song | Organizer: Peter Song |
| Session EO023 | Room: Virtual R1 |
| Modern multivariate methods for multifaceted data | Sunday 05.6.2022 08:00 - 10:05 |
| Chair: Anuradha Roy | Organizer: Anuradha Roy |
| Session EO293 | Room: Virtual R10 |
| Inference of hierarchical and nonparametric structures | Sunday 05.6.2022 08:00 - 10:05 |
| Chair: Minwoo Chae | Organizer: Long Nguyen |
| E0272: M. Chae | |
| Deep generative models for nonparametric estimation of singular distributions | |
| E0362: J. Miller, E. Weinstein | |
| Bayesian data selection | |
| E0547: Y. Wei, S. Mukherjee, L. Nguyen | |
| A unified framework for parameters estimation in finite mixture models | |
| E0535: S. Mano | |
| Max-infinitely divisible processes with exchangeability and their inference | |
| E0698: N.P.M. Ho | |
| On the multivariate Fourier integral theorem: Statistical and methodological perspectives |
| Session EO409 | Room: Virtual R11 |
| Modern statistical methods for complex data analysis | Sunday 05.6.2022 08:00 - 10:05 |
| Chair: Pai-Ling Li | Organizer: Jeng-Min Chiou |
| E1036: Y. Kim, I. Kong, J. park | |
| Sparse Bayesian CNN | |
| E0860: C.-T. Chiang | |
| Semi-supervised learning using elliptical distributions with unknown density generators | |
| E0845: H. Matsui | |
| Truncated estimation for functional linear model and its application to agricultural data | |
| E0710: P.-L. Li, J.-M. Chiou | |
| Generalized linear model with functional covariate and its derivatives |
| Session EO061 | Room: Virtual R12 |
| New horizons in longitudinal studies | Sunday 05.6.2022 08:00 - 10:05 |
| Chair: MinJae Lee | Organizer: Hyunkeun Cho |
| E0657: E. Hector, J. Wang, L. Luo | |
| Statistical inference for streamed longitudinal data | |
| E0795: S. Kim, S. Wang, H. Cho, W. Chang | |
| Predictive model for sparse longitudinal data | |
| E0968: X. Dai, J. Qiu, Z. Zhu | |
| Nonparametric estimation of repeated densities with heterogeneous sample sizes | |
| E1037: J. Ahn | |
| Bayesian analysis of longitudinal dyadic/multiple outcome data with informative missing data |
| Session EO289 | Room: Virtual R13 |
| Estimation and hypothesis testing | Sunday 05.6.2022 08:00 - 10:05 |
| Chair: Xuejun Jiang | Organizer: Xuejun Jiang |
| E0598: J. Jiang | |
| Nonnested model selection based on empirical likelihood ratio | |
| E0175: Y. Tang | |
| Multiply robust estimation of quantile treatment effects with missing responses | |
| E0919: F. Chen, W. Rao, X. Liu | |
| Local influence analysis for the sliced average third-moment estimation | |
| E0973: P. Liu | |
| Robust estimation and test for Pearson's correlation coefficient |
| Session EO043 | Room: Virtual R2 |
| Machine learning and stability | Sunday 05.6.2022 08:00 - 10:05 |
| Chair: Andreas Christmann | Organizer: Andreas Christmann |
| E0205: Y. Ying | |
| Simple stochastic and online gradient decent algorithms for pairwise learning | |
| E0283: B. Sriperumbudur | |
| Johnson & Lindenstrauss meet Hilbert at a Kernel | |
| E0330: X. Guo, X. Chen, B. Tang, J. Fan, Z.-C. Guo, L. Shi | |
| Convergence of stochastic gradient descent algorithms for functional data learning | |
| E0203: A. Christmann | |
| Qualitative robustness of divide-and-conquer methods for large data sets |
| Session EO233 | Room: Virtual R3 |
| New challenges for sparse methods | Sunday 05.6.2022 08:00 - 10:05 |
| Chair: Qing Mai | Organizer: Qing Mai |
| E0182: Q. Li | |
| An efficient greedy search algorithm for high-dimensional linear discriminant analysis | |
| E0270: N. Wang, Q. Mai, X. Zhang | |
| Tensor t distribution and tensor response regression | |
| E0303: Y. Gu, H. Zou | |
| Sparse composite quantile regression with consistent parameter tuning | |
| E0306: Q. Mai | |
| A doubly-enhanced EM algorithm for model-based tensor clustering | |
| E0700: J. Wang | |
| Signed network embedding and its applications to detection of communities and anomalies |
| Session EO249 | Room: Virtual R4 |
| Trend and change-point analysis in time series | Sunday 05.6.2022 08:00 - 10:05 |
| Chair: Kin Wai Chan | Organizer: Kin Wai Chan |
| E0312: L. Chen, J. Li, W. Wang, W.B. Wu | |
| $L_2-L_\infty$ inference of breaks for high dimensional time series | |
| E0315: R. Wang, X. Shao, S. Volgushev, C. Zhu | |
| Statistical inference for change points in high-dimensional data | |
| E0542: H.K. To, K.W. Chan | |
| Inference of signal variance in time series for mean stationarity test | |
| E0321: F. Jiang, Z. Zhao, X. Shao | |
| Segmenting time series via self-normalization | |
| E0539: K.W. Chan, C.H. Cheng | |
| A general framework for constructing locally self-normalized multiple-change-point tests |
| Session EO401 | Room: Virtual R5 |
| Machine learning using experimental design ideas | Sunday 05.6.2022 08:00 - 10:05 |
| Chair: Lin Wang | Organizer: Lin Wang |
| E0619: Q. Xiao | |
| A scalable Gaussian process for large-scale periodic data | |
| E0764: X. Zhang, Z. Qi, R. Miao | |
| Proximal learning for individualized treatment regimes under unmeasured confounding | |
| E0635: N.M. Xi | |
| scSampler: Fast diversity-preserving subsampling of large-scale single-cell transcriptomic data | |
| E0914: C. Shi, B. Tang | |
| Model-robust subdata selection for big data | |
| E0727: L. Wang | |
| Balanced subsampling for big data with categorical predictors |
| Session EO365 | Room: Virtual R6 |
| Advanced methods in large-scale biomedical data analysis | Sunday 05.6.2022 08:00 - 10:05 |
| Chair: Bingxin Zhao | Organizer: Bingxin Zhao |
| E0468: G. Li | |
| Integration of imaging and sequencing data in the context of visual cell sorting | |
| E0491: Z. Yu | |
| BRIDGE: A novel transcriptome-wide association analysis framework for biomarker identification | |
| E0622: Y. Zhang, D. Gan, G. Yin | |
| The graphical R2D2 estimator for the precision matrices | |
| E0652: L. Feng | |
| SKPD: A general framework of signal region detection in image regression | |
| E0683: X. Li, Z. Li, X. Lin | |
| Scalable rare variant meta-analysis of sequencing studies using summary statistics and functional annotations |
| Session EO419 | Room: Virtual R7 |
| Interval-censored failure time data (for Jianguo Sun 60th birthday) | Sunday 05.6.2022 08:00 - 10:05 |
| Chair: Yang-Jin Kim | Organizer: Yang-Jin Kim |
| E0324: Y. Li, B. Zhang | |
| Semiparametric analysis of multivariate recurrent events with informative censoring | |
| E0366: H. Wang | |
| Optimal subsampling for massive survival data | |
| E0789: Y.-J. Kim | |
| Prediction accuracy for joint model of interval-censored data and longitudinal markers | |
| E0812: D. Park | |
| Joint modeling of multivariate longitudinal data and recurrent events: Application to the urea cycle disorders study | |
| E0872: L. Wang, Y. Mao, X. sui | |
| Bayesian joint analysis of longitudinal data and interval-censored failure time data |
| Session EO133 | Room: Virtual R8 |
| Machine learning for modern data | Sunday 05.6.2022 08:00 - 10:05 |
| Chair: Hongxiao Zhu | Organizer: Hongxiao Zhu |
| E0341: A. Bui | |
| Dimension reduction with prior information for knowledge discovery | |
| E0360: J. Heng, A. Doucet, V. De Bortoli, J. Thorton | |
| Diffusion Schrodinger bridge with applications to score-based generative modeling | |
| E0641: H. Zhu, S. Huo | |
| Model data heterogeneity with Dirichlet diffusion trees | |
| E0756: K. Fallah, M. Connor, C. Rozell | |
| Learning the data manifold for reusable augmentations | |
| E0685: Y. Wei | |
| Minimum L1 interpolators: Precise asymptotics and multiple descent |
| Session EO073 | Room: Virtual R9 |
| Advances in nonparametric and semiparametric panel data models | Sunday 05.6.2022 08:00 - 10:05 |
| Chair: Alexandra Soberon | Organizer: Alexandra Soberon |
| E0220: L.A. Arteaga Molina, J.M. Rodriguez-Poo | |
| Testing beta constancy in asset pricing models | |
| E0281: D. Henderson | |
| Estimation of a varying coefficient, fixed-effects Cobb-Douglas production function in levels | |
| E0349: J. Schnurbus, H. Haupt | |
| Nonparametric modeling of environmental time series distributions | |
| E0500: A.A.Y. Pua, M. Fritsch, J. Schnurbus | |
| Practical aspects of using quadratic moment conditions in linear dynamic panel data models | |
| E0264: A. Soberon, W. Stute | |
| Measurement errors in panel data regression: A direct estimation approach |
| Parallel session G: EcoSta2022 | Sunday 05.6.2022 | 10:35 - 12:15 |
| Session EO373 | Room: 101 (Hybrid 1) |
| Advances in change-point detection methods | Sunday 05.6.2022 10:35 - 12:15 |
| Chair: Ali Shojaie | Organizer: Ali Shojaie |
| E0227: O.H. Madrid Padilla | |
| Change point localization in dependent dynamic nonparametric random dot product graph | |
| E0790: Y. Liu | |
| Detection of relevant changes in the frequency domain | |
| E1031: G. Michailidis | |
| Multiple change point detection in reduced rank high dimensional vector autoregressive models | |
| E0844: D. Cheng, Z. He, Y. Zhao | |
| Multiple testing of local extrema for detection of structural breaks in linear models |
| Session EO307 | Room: 102 (Hybrid 2) |
| Recent advances in econometrics and machine learning | Sunday 05.6.2022 10:35 - 12:15 |
| Chair: Komsan Suriya | Organizer: Qingfeng Liu |
| Session EO383 | Room: 103 (Hybrid 3) |
| Recent developments in high-dimensional data analysis (virtual) | Sunday 05.6.2022 10:35 - 12:15 |
| Chair: Zhihua Su | Organizer: Zhihua Su |
| E0208: Y. Dong | |
| Testing the linear mean and constant variance conditions in sufficient dimension reduction | |
| E0319: K. Kim | |
| On sufficient graphical models | |
| E0320: L. Xue, Q. Zhang, B. Li | |
| Dimension reduction and data visualization for Frechet regression | |
| E0807: B. Li, K.-Y. Lee, L. Li | |
| Functional directed acyclic graphs |
| Session EO237 | Room: 104 (Hybrid 4) |
| Recent advances in statistical inference | Sunday 05.6.2022 10:35 - 12:15 |
| Chair: Gourab Mukherjee | Organizer: Gourab Mukherjee |
| E0694: B. Bhattacharya, S. Das, S. Mukherjee | |
| Motif estimation via subgraph sampling: The fourth-moment phenomenon | |
| E0766: S. Mukherjee, N. Deb, R. Mukherjee, M. Yuan | |
| Global testing for dependent Bernoullis | |
| E0874: R. Mukherjee | |
| On PC adjustments for high dimensional association studies | |
| E0962: S. Chatterjee | |
| Cross-validation for signal denoising |
| Session EO295 | Room: 105 (Hybrid 5) |
| Theory and algorithms for high-dimensional regression for big data (virtual) | Sunday 05.6.2022 10:35 - 12:15 |
| Chair: Peng Zeng | Organizer: Peng Zeng |
| E0293: H. Zhou, J. Zhou, G. Li | |
| A robust joint model of longitudinal trajectories and time-to-event data at biobank scale | |
| E0606: N. Lin, Y. Fan | |
| Residual projection for quantile regression | |
| E0877: P. Zeng | |
| ODE-on-scalar regression with an application on COVID-19 data | |
| E0993: H. Zhang | |
| Outlier detection in robust regression via chance-constrained programming |
| Session EO367 | Room: 106 (Hybrid 6) |
| Recent advances in complex network analysis | Sunday 05.6.2022 10:35 - 12:15 |
| Chair: Yuan Zhang | Organizer: Yunpeng Zhao |
| E0188: Y. Zhang | |
| L-2 regularized maximum likelihood for beta-model estimation in large and sparse networks | |
| E0631: X. Li, Y. Zhao, Q. Pan, N. Hao | |
| Heterogeneous block covariance model for community detection | |
| E0869: J. Nishimura, Y. Zhao | |
| Classically boosted network embeddings | |
| E0920: B. Jiang | |
| An autoregressive beta-model for dynamic networks |
| Session EO281 | Room: 107 (Hybrid 7) |
| Advances in functional data and networks analysis | Sunday 05.6.2022 10:35 - 12:15 |
| Chair: Jeng-Min Chiou | Organizer: Jane-Ling Wang |
| E0581: P. Dubey | |
| Modeling time-varying random objects and dynamic networks | |
| E0736: K. Kato, Y. Sasaki, H. Chiang | |
| Inference for high-dimensional exchangeable arrays with an application to network data | |
| E0454: Q. Zhong, Z. Lin, J.-L. Wang | |
| Basis expansions for functional snippets | |
| E0793: F. Yao, Y. Yang | |
| Online estimation for functional data |
| Session EO363 | Room: Virtual R1 |
| Recent advances in statistical learning and statistical modeling | Sunday 05.6.2022 10:35 - 12:15 |
| Chair: Jiwei Zhao | Organizer: Jiwei Zhao |
| E0224: T. Ghosh, M. Yu, J. Zhao | |
| Optimal estimation of average treatment effect on the treated under endogeneous treatment assignment | |
| E0209: G. Xu, G. Fang, H. Xu, X. Zhu, Y. Guan | |
| Group network Hawkes process | |
| E0340: S. Ma | |
| Causal inference via artificial neural networks: From prediction to causation | |
| E0210: X. Bi, X. Shen | |
| Distribution-invariant differential privacy |
| Session EO361 | Room: Virtual R10 |
| Semiparametric methods for causal inference | Sunday 05.6.2022 10:35 - 12:15 |
| Chair: Kendrick Li | Organizer: Kendrick Li, Xu Shi |
| E0335: Y. Cui, M. Kosorok, E. Sverdrup, S. Wager, R. Zhu | |
| Estimating heterogeneous treatment effects with right-censored data via causal survival forests | |
| E0486: B. Sun, Z. Liu, E. Tchetgen Tchetgen | |
| Semiparametric efficient G-estimation with invalid instrumental variables | |
| E0866: K. Li, X. Shi, W. Miao, E. Tchetgen Tchetgen | |
| Double negative control inference in test-negative design studies of vaccine effectiveness | |
| E0852: W. Miao | |
| Semiparametric data fusion with external summary statistics |
| Session EO407 | Room: Virtual R11 |
| Ecological statistics | Sunday 05.6.2022 10:35 - 12:15 |
| Chair: Wen-Han Hwang | Organizer: Wen-Han Hwang |
| E0594: J. Stoklosa | |
| A general algorithm for error-in-variables modelling using monte carlo expectation maximization | |
| E0623: N. Sibanda | |
| Multispecies occupancy modelling of New Zealand bird species | |
| E0625: Y. Wang, C. Samarasekara, L. Stone | |
| A machine learning method for estimating the probability of presence using presence-background data | |
| E0620: W.-H. Hwang | |
| On the occupancy models with time-to-detection data |
| Session EO345 | Room: Virtual R12 |
| Modern statistical methods for experimental design | Sunday 05.6.2022 10:35 - 12:15 |
| Chair: Ming-Chung Chang | Organizer: Ming-Chung Chang |
| E0662: C.-L. Sung | |
| Multi-fidelity surrogate modeling with confidence: Stacking experimental design with cost complexity guarantees | |
| E0583: C.-Y. Sun, B. Tang | |
| Uniform projection designs and strong orthogonal arrays | |
| E0820: L.-H. Lin | |
| Simulator selection with applications in cell biology | |
| E0564: S.-F. Tsai | |
| Generating optimal order-of-addition designs with flexible run sizes |
| Session EO153 | Room: Virtual R13 |
| Statistical approaches for functional observations | Sunday 05.6.2022 10:35 - 12:15 |
| Chair: Ci-Ren Jiang | Organizer: Ci-Ren Jiang |
| E0248: C.-R. Jiang, E. Lila, J. Aston, J.-L. Wang | |
| Eigen-adjusted functional principal component analysis | |
| E0309: W.-K. Seo | |
| Functional principal component analysis of cointegrated functional time series | |
| E0496: H.L. Shang | |
| Geometrically weighted compositional data analysis for forecasting life-table death counts | |
| E0737: M.-Y. Huang | |
| Partially linear models for functional data |
| Session EO031 | Room: Virtual R2 |
| Multidimensional/multimodal neuroimaging data analysis | Sunday 05.6.2022 10:35 - 12:15 |
| Chair: Yi Zhao | Organizer: Yi Zhao |
| E0184: F. Zhang | |
| Statistical modeling issues in brain age prediction | |
| E0225: B. Risk, R. Murden, G. Tian, D. Qiu | |
| Probabilistic joint and individual variation explained | |
| E0234: Y. Zhao | |
| Neurodevelopment subtyping via multidimensional brain functional connectomes | |
| E0616: B. Caffo | |
| Multidimensional/multimodal neuroimaging data analysis |
| Session EO077 | Room: Virtual R3 |
| Causal inference | Sunday 05.6.2022 10:35 - 12:15 |
| Chair: Yen-Tsung Huang | Organizer: Yen-Tsung Huang |
| E0516: J. Young | |
| Causal inference, competing events, and mechanism | |
| E0984: E. Ogburn | |
| Disentangling confounding and nonsense associations due to dependence | |
| E0997: K.C.G. Chan, F. Xia | |
| Identification and estimation of natural mediation effect in the presence of treatment induced confounding | |
| E1005: S.-H. Lin | |
| From linear structural equation modeling to generalized multiple mediation formula |
| Session EO243 | Room: Virtual R4 |
| New ideas in empirical Bayes | Sunday 05.6.2022 10:35 - 12:15 |
| Chair: Sihai Zhao | Organizer: Sihai Zhao |
| E0580: M. Stephens | |
| Adventures in sparsity and shrinkage with the normal means model | |
| E0730: N. Ignatiadis, S. Wager | |
| Covariate-powered empirical Bayes estimation | |
| E0818: A. Barbehenn, S. Zhao | |
| Asymptotically optimal simultaneous gaussian mean estimation with nonparametric regression | |
| E0978: W. Sun | |
| A nonparametric integrative Tweedie approach to empirical Bayes estimation with side information |
| Session EO219 | Room: Virtual R5 |
| High-dimensional data analysis in econometrics and statistics | Sunday 05.6.2022 10:35 - 12:15 |
| Chair: Sungkyu Jung | Organizer: Sungkyu Jung, Jeongyoun Ahn |
| E0703: K. Yata, A. Ishii, M. Aoshima | |
| Estimation of eigenvectors for linear combinations of high-dimensional covariance matrices and its application | |
| E0713: S.J. Shin | |
| Principal weighted least square support vector machine: An online dimension-reduction tool for binary classification | |
| E0946: L. Goldberg, A. Shkolnik, A. Kercheval | |
| James-Stein for eigenvectors | |
| E0945: A. Shkolnik, Y. Lee | |
| Direction penalized principal component analysis |
| Session EO205 | Room: Virtual R6 |
| Fair, robust, efficient and explainable machine learning models | Sunday 05.6.2022 10:35 - 12:15 |
| Chair: Yao Li | Organizer: Yao Li |
| E0231: Y. Sun | |
| Does enforcing fairness mitigate algorithmic biases due to distributional shift? | |
| E0325: Y. Li, T. Tang, T. Lee, C.-J. Hsieh | |
| Detecting adversarial examples with Bayesian neural network | |
| E0453: J. Zheng | |
| Time-frequency analysis of scalp EEG with Hilbert-Huang transform and deep learning | |
| E0492: H. Zhang | |
| How to trust a black-box: Formal verification of deep neural networks |
| Session EO253 | Room: Virtual R7 |
| Recent advances in survival analysis | Sunday 05.6.2022 10:35 - 12:15 |
| Chair: Sy Han Chiou | Organizer: Sy Han Chiou |
| E0503: L.-P. Chen, B. Qiu | |
| Boosting method for length-biased and interval-censored survival data subject to high-dimensional error-prone covariates | |
| E0638: H. Chen, C.-F. Tang | |
| Goodness-of-fit test for Cox model under isotonic constraint | |
| E0761: Y. Chen, C.-F. Tang, S.H. Chiou, M. Chen | |
| Weighted least squares estimation for semiparametric accelerated failure time model with regularization | |
| E1043: J. Qian, S.H. Chiou, R. Betensky | |
| Transformation model based regression with dependently truncated and independently censored data |
| Session EO337 | Room: Virtual R8 |
| Innovative methods for graphical models and networks | Sunday 05.6.2022 10:35 - 12:15 |
| Chair: Jeffrey Morris | Organizer: Jeffrey Morris |
| E0885: N. Desai, J. Morris, V. Baladandayuthapani | |
| Connectivity regression | |
| E0985: F. Zhou | |
| Functional Bayesian networks | |
| E0989: T.-H. Yao, Z. Wu, K. Bharath, J. Li, V. Baladandayuthapani | |
| Probabilistic learning of treatment trees in cancer | |
| E0986: L. Zhang | |
| Bayesian functional graphical model for dynamic functional connectivity network inference |
| Session EO019 | Room: Virtual R9 |
| Recent developments in complex imaging data analysis | Sunday 05.6.2022 10:35 - 12:15 |
| Chair: Dayu Sun | Organizer: Dayu Sun |
| Parallel session H: EcoSta2022 | Sunday 05.6.2022 | 13:15 - 14:55 |
| Session EV463 | Room: Virtual R7 |
| Contributions in causal inference | Sunday 05.6.2022 13:15 - 14:55 |
| Chair: Subir Ghosh | Organizer: EcoSta |
| E0814: H. Xie | |
| Nonlinear and nonseparable structural functions in fuzzy regression discontinuity designs | |
| E0825: K. Fusejima, T. Ishihara, M. Sawada | |
| Joint diagnostic test of regression discontinuity designs: multiple testing problem | |
| E0947: A. Srakar | |
| Fuzzy Wald ratio difference-in-differences and changes-in-changes estimator for spatiotemporal and spatial data | |
| E0743: J. Bethaeuser | |
| Causal impact of policy measures and behavior on the COVID pandemic in Germany |
| Session EO055 | Room: 101 (Hybrid 1) |
| Recent advances in high-dimensional covariance estimation | Sunday 05.6.2022 13:15 - 14:55 |
| Chair: Kei Hirose | Organizer: Kei Hirose |
| E0380: B. Poignard, Y. Terada | |
| Asymptotic theory of sparse factor models in high-dimension | |
| E0644: P.-H. Huang | |
| Accelerating dependency modeling with graphics processing units | |
| E0744: S. Kawano, K. Yoshikawa | |
| Multilinear common component analysis for tensor data based on Kronecker product approach | |
| E0781: W. Yoshida, K. Hirose | |
| Computationally efficient forecasting algorithm in the SUTSE model and its properties |
| Session EO411 | Room: 102 (Hybrid 2) |
| Statistical learning for functional data | Sunday 05.6.2022 13:15 - 14:55 |
| Chair: Yousri Slaoui | Organizer: Sophie Dabo, Yousri Slaoui |
| E0760: Y. Slaoui | |
| Unsupervised classification method based on nonparametric functional mode estimation | |
| E0796: L. Grill, Y. Slaoui, D. Nortershauser, S. Le Masson | |
| Using Bayesian neural network as an actor in actor-critic methods | |
| E0802: O. Ben Mrad, Y. Slaoui, A. Masmoudi | |
| Statistical learning in nonparametric q-kernel q-density estimation | |
| E0895: S. El Adlouni | |
| Manifold MCMC algorithm for Gamma-GPD mixture model |
| Session EO041 | Room: 103 (Hybrid 3) |
| Theories and methodologies for high-dimensional data | Sunday 05.6.2022 13:15 - 14:55 |
| Chair: Kazuyoshi Yata | Organizer: Kazuyoshi Yata |
| E0643: Y. Nakayama, K. Yata, M. Aoshima | |
| Test for outlier detection by high-dimensional PCA | |
| E0773: R. Oda, H. Yanagihara | |
| Condition of GIC to select the model minimizing KL-loss function in high-dimensional multivariate linear regression | |
| E0915: Y. Umezu | |
| Non-linear variable selection via kernel regression with high-dimensionality | |
| E0414: K. Tsukuda, S. Matsuura | |
| Testing allometric extension in high-dimensional and spiked eigenvalue situations |
| Session EO191 | Room: 104 (Hybrid 4) |
| Statistical inference on various manifold | Sunday 05.6.2022 13:15 - 14:55 |
| Chair: Toshihiro Abe | Organizer: Toshihiro Abe |
| E0517: Y. Miyata, T. Shiohama, T. Abe | |
| An extended sine-skewed circular distribution and its extension to a model on cylinder | |
| E0521: T. Shiohama, T. Shiohama | |
| Complex valued time series modeling in relation to directional statistics | |
| E0540: T. Imoto | |
| Construction of a circular distribution from a discrete distribution and its extension | |
| E0601: Y. Tsuruta | |
| Smoothing parameter selection of circular kernel density estimation |
| Session EO331 | Room: 105 (Hybrid 5) |
| Recent development on functional analysis of complex data | Sunday 05.6.2022 13:15 - 14:55 |
| Chair: Weichi Wu | Organizer: Weichi Wu |
| E0185: Z. Lin, Y. Lin | |
| A unified approach to hypothesis testing for functional linear models | |
| E0666: Y. Zhang, H. Zhu, Y. Li, H. Lian | |
| Semiparametric function-on-function quantile regression model with dynamic single-index interactions | |
| E0816: Y. Cui, Z. Zhou | |
| Optimal forecasting for locally stationary functional time series using double-sieve method | |
| E1000: R. Tan, W. Huang, G. Yin, Z. Zhang | |
| Estimation of functional treatment effect using generalized empirical likelihood stabilized weights |
| Session EO339 | Room: Virtual R1 |
| Nature-inspired metaheuristic methods and applications | Sunday 05.6.2022 13:15 - 14:55 |
| Chair: Frederick Kin Hing Phoa | Organizer: Frederick Kin Hing Phoa |
| E0771: H. Liu, F.K.H. Phoa, J.Y.H. Chen-Burger, S.P. Lin | |
| Metaheuristic optimization on tensor-type solution via swarm intelligence | |
| E0828: H. Sutrisno, F.K.H. Phoa | |
| Finding time series motif by using swarm intelligence method | |
| E0931: C.-H. Huang, F.K.H. Phoa | |
| An efficient method to scatter network nodes on a spherical surface via swarm intelligence | |
| E0992: P.-C. Yen, F.K.H. Phoa | |
| Traveling salesman problem via swarm intelligence |
| Session EO177 | Room: Virtual R10 |
| Recent developments on data integration for statistics | Sunday 05.6.2022 13:15 - 14:55 |
| Chair: Anne Ruiz-Gazen | Organizer: Estelle Medous, Anne Ruiz-Gazen |
| E0792: T. Laurent, A. Vanhems, V.H. Do | |
| Guidelines on areal interpolation methods | |
| E0934: M. Peruzzi, D. Dunson | |
| Spatial multivariate trees for integrating geospatial data from multiple sources | |
| E0939: A. Ruiz-Gazen, E. Medous, C. Goga, J.-F. Beaumont, A. Dessertaine, P. Puech | |
| Improving finite population inference by data integration | |
| E0937: E. Medous, A. Ruiz-Gazen, C. Goga, J.-F. Beaumont, A. Dessertaine, P. Puech | |
| Statistical data integration using a prediction approach |
| Session EO317 | Room: Virtual R2 |
| Advances in statistical methods for reliability analysis | Sunday 05.6.2022 13:15 - 14:55 |
| Chair: Man Ho Ling | Organizer: Man Ho Ling |
| E0189: E. Castilla | |
| Robust statistical inference for one-shot devices | |
| E0290: C.-T. Lin, C.-C. Tsai, N. Balakrishnan | |
| Lamination scheme of curing degree at multiple levels of temperature with location-scale regression | |
| E0809: D. Mitra | |
| Order restricted inference for adaptive progressively censored competing risks data | |
| E0921: H. Nagatsuka, N. Balakrishnan | |
| Interval estimation and hypothesis testing for the generalized Pareto distribution under non-regularity conditions |
| Session EO021 | Room: Virtual R3 |
| Recent advances in spatial scan statistics | Sunday 05.6.2022 13:15 - 14:55 |
| Chair: Matthieu Marbac | Organizer: Matthieu Marbac |
| E0195: T. Zhang | |
| Spatial scan statistics in statistical models | |
| E0276: L. Cucala | |
| Multivariate scan statistics for spatial data | |
| E0294: P.-S. Lin | |
| Identification of geographic clusters for temporal heterogeneity with application to dengue surveillance | |
| E0541: M.S. Ahmed, M. Genin, M. Marbac | |
| A new spatial scan statistic for multiple spatial clusters |
| Session EO059 | Room: Virtual R4 |
| Blockchain, digital currencies, and decentralised finance | Sunday 05.6.2022 13:15 - 14:55 |
| Chair: Stephen Chan | Organizer: Stephen Chan, Jeffrey Chu |
| E0553: Y. Chen | |
| Topological data analysis of dynamic Ethereum token networks | |
| E0574: Y. Gong, R. Huser | |
| Asymmetric tail dependence modeling, with application to cryptocurrency market data | |
| E1010: S. Chan, J. Chu, Y. Zhang | |
| An analysis of the return-volume relationship in decentralized finance (DeFi) | |
| E0497: B. Hadji Misheva, J. Osterrieder, A. Hirsa | |
| eXplainable AI for credit risk management |
| Session EO149 | Room: Virtual R5 |
| Spatio-temporal models for environmental and health applications | Sunday 05.6.2022 13:15 - 14:55 |
| Chair: Chae Young Lim | Organizer: Stefano Castruccio |
| E0268: J. Park, W. Chang, B. Choi | |
| An interaction Neyman-Scott point process model for COVID-19 | |
| E0275: Z. Qu, W. Dai, M. Genton | |
| Robust Two-Layer Partition Clustering of Sparse Multivariate Functional Data | |
| E0515: W. Huang, A. Monahan, F. Zwiers | |
| Estimating concurrent climate extremes: A conditional approach | |
| E0576: Y. Guan, G. Page, B. Reich, M. Ventrucci, S. Yang | |
| A spectral adjustment for spatial confounding |
| Session EO440 | Room: Virtual R6 |
| Some recent developments in high dimensional statistics | Sunday 05.6.2022 13:15 - 14:55 |
| Chair: Lei Huang | Organizer: Lei Huang |
| E0271: X. Fang | |
| High-dimensional central limit theorems by Stein's method | |
| E0286: X. Xia | |
| Relative error-based model averaging | |
| E0430: C. Wang | |
| Limiting spectral distribution of large dimensional Spearman's rank correlation matrices | |
| E0490: C. Wang, T. Mei, J. Yao | |
| On singular values of data matrices with general independent columns |
| Session EO255 | Room: Virtual R8 |
| Design and analysis of screening experiments | Sunday 05.6.2022 13:15 - 14:55 |
| Chair: Rakhi Singh | Organizer: Rakhi Singh |
| E0523: V. Syrotiuk | |
| Screening using locating arrays | |
| E0467: A. Vazquez, W.K. Wong, P. Goos | |
| Effective algorithms for constructing two-level QB-optimal designs for screening experiments | |
| E0372: J.-W. Huang, F.K.H. Phoa, Y.-W. Chen | |
| A factor screening approach for supersaturated experiments with an exponential family response via Dantzig selector 2.0 | |
| E0656: S. Gilmour, P.-W. Tsai | |
| Optimal two-level designs under model uncertainty |
| Session EO071 | Room: Virtual R9 |
| Recent developments in statistical deep learning | Sunday 05.6.2022 13:15 - 14:55 |
| Chair: Il Do Ha | Organizer: Il Do Ha |
| E0570: J.-M. Kim, I.D. Ha | |
| Deep learning-based residual control chart for count data | |
| E0589: J.E. Choi, D. Shin | |
| An ensemble model of CNN-BiLSTMs for forecasting NASDAQ volatility index | |
| E0721: A. McInerney, K. Burke | |
| Variable and architecture selection in neural networks | |
| E0821: I.D. Ha, J. Kim | |
| Understanding deep learning via statistical modelling approaches |
| Parallel session I: EcoSta2022 | Sunday 05.6.2022 | 15:25 - 16:40 |
| Session EV460 | Room: Virtual R2 |
| Contributions in applied econometrics | Sunday 05.6.2022 15:25 - 16:40 |
| Chair: James Flegal | Organizer: EcoSta |
| E0357: G. Milunovich | |
| Measuring the impact of cybersecurity breaches on bitcoin returns | |
| E0463: M. Modina, A. Bitetto, S. Filomeni | |
| Can unlisted firms benefit from market information? A data-driven approach | |
| E0679: R. Neck, D. Blueschke, K. Weyerstrass | |
| Optimal fiscal policies in booms and in recessions: An econometric case study for Slovenia |
| Session EV451 | Room: Virtual R6 |
| Contributions in computational statistics and applications | Sunday 05.6.2022 15:25 - 16:40 |
| Chair: Abdelaati Daouia | Organizer: EcoSta |
| E0922: S. Pal, C. Heumann | |
| A Gaussian mixture model with a modified Hard EM algorithm in clustering problems | |
| E0173: L. Nguyen | |
| Expectation-maximization algorithm with combinatorial assumption | |
| E0929: E. Kharatikoopaei, N. Akhter, A. Ellison, N. Richards, B. Obara, A. Kasim, S. Steve Bonner, E. McCauley, N. Mukerji | |
| The importance of morphology data in predicting the risks of aneurysm rupture |
| Session EV454 | Room: Virtual R7 |
| Contributions in financial econometrics | Sunday 05.6.2022 15:25 - 16:40 |
| Chair: Pavel Krupskiy | Organizer: EcoSta |
| E0748: M. Nicolas | |
| Spurious tail risk factors and asset prices | |
| E0881: K.K. Lawuobahsumo, B. Algieri, A. Leccadito | |
| Cryptocurrencies' quantile and tail expectation forecasting | |
| E0474: Y. Cai | |
| A novel approach to bank marketing campaign |
| Session EV459 | Room: Virtual R8 |
| Contributions in forecasting | Sunday 05.6.2022 15:25 - 16:40 |
| Chair: Matthieu Marbac | Organizer: EcoSta |
| E0323: A. Vasnev, J. Magnus | |
| On the uncertainty of a combined forecast: The critical role of correlation | |
| E0843: N. Wichitaksorn, G. Kapoor, W. Zhang | |
| Forecasting half-hourly electricity prices using a mixed-frequency VAR framework: The case of New Zealand market | |
| E0864: J.-B. Hasse, Q. Lajaunie | |
| Using the yield curve to forecast recessions: The role of fragmentation in the Euro area |
| Session EO081 | Room: 102 (Hybrid 2) |
| Gaussian approximation for high-dimensional data | Sunday 05.6.2022 15:25 - 16:40 |
| Chair: Yuta Koike | Organizer: Yuta Koike |
| E0344: D. Kurisu, K. Kato, X. Shao | |
| Gaussian approximation and spatially dependent wild bootstrap for high-dimensional spatial data | |
| E1046: L. Peng, G. Cheng | |
| Simultaneous bootstrap inference for high-dimensional spatial median with applications | |
| E0944: M. Imaizumi | |
| Hypothesis Test and Confidence Analysis with Wasserstein Distance on General Dimension |
| Session EO127 | Room: 103 (Hybrid 3) |
| Stochastic control and data science in economics and finance | Sunday 05.6.2022 15:25 - 16:40 |
| Chair: Seyoung Park | Organizer: Seyoung Park |
| E0442: J. Chae, B.-G. Jang, S. Park | |
| Optimal retirement with disability risk | |
| E0558: Q. Li | |
| A generalization of Ramsey's on discount rate with regime-switching by martingale approach | |
| E0590: C. He, A. Milne, S. Park | |
| Optimal consumption and savings decisions with disastrous income risk: Revisiting Rietz's rare disaster risk hypothesis |
| Session EO139 | Room: 104 (Hybrid 4) |
| Methods for survival data analysis II | Sunday 05.6.2022 15:25 - 16:40 |
| Chair: Takeshi Emura | Organizer: Takeshi Emura |
| Session EO065 | Room: 105 (Hybrid 5) |
| Inference for dynamic systems | Sunday 05.6.2022 15:25 - 16:40 |
| Chair: Francoise Anne Kemp | Organizer: Christophe Ley |
| E0801: M.N. Damian, R. Nijzink, C. Ley, S. Schymanski, J. Hale | |
| Using Bayes factors to compare dynamical models of hydrological systems | |
| E0974: F.A. Kemp, D. Proverbio, A. Aalto, C. Ley, J. Goncalves, A. Skupin, S. Magni | |
| Dynamical modelling of COVID-19 pandemic | |
| E0595: H. Shigemoto, T. Morimoto | |
| Dynamic conditional correlation models with time-varying parameters incorporating realized covariance matrices |
| Session EO017 | Room: Virtual R1 |
| Econometrics of spillover effects and social interactions | Sunday 05.6.2022 15:25 - 16:40 |
| Chair: Ryo Okui | Organizer: Ryo Okui |
| E0232: T. Yanagi, T. Hoshino | |
| Causal inference with noncompliance and unknown interference | |
| E0261: W. Wang | |
| Recovering latent linkage structures and spillover effects with structural breaks in panel data models | |
| E0285: C. Yang | |
| Production network positions and risk premia: A semiparametric approach |
| Session EO155 | Room: Virtual R3 |
| Recent advances in financial econometrics | Sunday 05.6.2022 15:25 - 16:40 |
| Chair: Seok Young Hong | Organizer: Seok Young Hong |
| E0709: S. Yu, Y. Li, I. Nolte, S. Nolte | |
| Testing for jumps in a discretely observed price process with endogenous sampling times | |
| E0712: X. Zhao, J. Sun, Y. Hong, O. Linton, X. Zhao | |
| Adjusted-range self-normalized autocorrelation tests | |
| E0886: Y. Li, I. Nolte, S. Nolte | |
| The Maximal Range-Return Divergence Statistic |
| Session EO187 | Room: Virtual R4 |
| Statistical methodology for personalising online content | Sunday 05.6.2022 15:25 - 16:40 |
| Chair: Cristina Mollica | Organizer: Ida Scheel |
| E0501: J. Grant, D. Leslie | |
| Learning to rank under multinomial logit choice | |
| E0510: S. Eide | |
| Recommender systems, bandits and Bayesian neural networks | |
| E0977: Q. Liu | |
| Pseudo-Mallows for preference learning and personalized recommendation |
| Session EO161 | Room: Virtual R5 |
| Copula models and applications | Sunday 05.6.2022 15:25 - 16:40 |
| Chair: Aurora Gatto | Organizer: Aurora Gatto, Fabrizio Durante |
| E0784: H. Wang, R. Chen | |
| The impact of COVID-19 pandemic shock on the correlation between energy markets and EU ETS | |
| E0870: A. Gatto, F. Durante, E. Perrone | |
| Kendall conditional value-at-risk with application to the Italian energy market | |
| E1034: N. Dietrich, J. Fernandez Sanchez, W. Trutschnig | |
| Convergence of copulas revisited: Different notions of convergence and their interrelations |
| Session EC461 | Room: 101 (Hybrid 1) |
| Contributions in Bayesian methods (in-person) | Sunday 05.6.2022 15:25 - 16:40 |
| Chair: Shogo Nakakita | Organizer: EcoSta |
| E0833: Y. Aizawa, H. Michimae | |
| Bayesian ridge estimators based on copula-based joint prior distributions for logistic regression parameters | |
| E0908: Y. Kakikawa, K. Shimamura, S. Kawano | |
| Bayesian fused lasso and Bayesian HORSES via horseshoe prior | |
| E0513: K. Kamatani, X. Song | |
| Haar-Weave-Metropolis kernel |
| Session EC432 | Room: 106 (Hybrid 6) |
| Contributions in high dimensional and complex data | Sunday 05.6.2022 15:25 - 16:40 |
| Chair: Kazuyoshi Yata | Organizer: EcoSta |
| E0677: L. Kontoghiorghes, A. Colubi | |
| Testing the equality of topic distribution between documents of a corpus | |
| E0983: Y. Okhrin | |
| Monitoring time dependent image processes | |
| E0734: A. Okazaki, S. Kawano | |
| Multi-task learning for compositional data based on sparse network lasso regularization |
| Session EC431 | Room: 107 (Hybrid 7) |
| Contributions in time series and applied econometrics (in-person) | Sunday 05.6.2022 15:25 - 16:40 |
| Chair: Junichi Hirukawa | Organizer: EcoSta |
| E0228: B. Sanhaji | |
| Nonlinear scalar BEKK | |
| E0903: Y. Ma, A. Anastasiou, T. Wang, F. Montiel | |
| Detecting change-points in noisy data sequences with continuous piecewise structures | |
| E1044: H. Mizobuchi, V. Zelenyuk | |
| A Measurement index: Proper or Not? |
| Parallel session J: EcoSta2022 | Sunday 05.6.2022 | 16:50 - 18:30 |
| Session EV457 | Room: Virtual R5 |
| Contributions in time series II | Sunday 05.6.2022 16:50 - 18:30 |
| Chair: Philip Yu | Organizer: EcoSta |
| E0850: V. Kuntze, H. Nyberg, S. Rauhala | |
| Similarity-based recession predictions in different monetary policy conditions | |
| E0718: M.A. Ruiz Reina | |
| Time series entropy: Clustering for decision-making | |
| E0669: J. Caiado, F. Santos | |
| A clustering approach for analysing the impact of COVID-19 on stock market volatility | |
| E0842: E. Kurozumi, A. Skrobotov | |
| On the asymptotic behavior of bubble date estimators |
| Session EI011 | Room: 101 (Hybrid 1) |
| Risk measurement for sustainable finance (virtual) | Sunday 05.6.2022 16:50 - 18:30 |
| Chair: Monica Billio | Organizer: Monica Billio |
| E0297: M. Billio, M. Guidolin, F. Rocciolo | |
| Responsible investing under ambiguity induced by climate risk | |
| E0714: F. Giancaterini, C. Morana, A. Hecq | |
| Is climate change time reversible? | |
| E0578: M. Costola, M. Billio, C. Latino, L. Pelizzon | |
| Measuring the relationship between ESG factors and firm's credit risk in Europe |
| Session EO203 | Room: 102 (Hybrid 2) |
| The Stein method and applications | Sunday 05.6.2022 16:50 - 18:30 |
| Chair: Xiao Fang | Organizer: Xiao Fang |
| E0274: W. Xu | |
| A unifying view on kernel stein discrepancy tests for goodness-of-fit | |
| E0519: Y. Koike | |
| Asymptotic mixed normality of the realized covariance matrix in high-dimensions | |
| E0548: S. Liu, Z.-S. Zhang | |
| Cramer-type moderate deviations under local dependence | |
| E0716: L. Xu | |
| Approximations to the ergodic measure of stable SDE via EM scheme |
| Session EO353 | Room: 103 (Hybrid 3) |
| Data science and other developments in financial modelling | Sunday 05.6.2022 16:50 - 18:30 |
| Chair: Rogemar Mamon | Organizer: Rogemar Mamon |
| E0565: C. Erlwein-Sayer, S. Grimm | |
| LSTM in varying regimes: How to combine hidden Markov and machine learning models for financial risk management | |
| E0633: H. Xiong | |
| A residual network for valuing large portfolios of variable annuities | |
| E0767: D.M. Rodrigo | |
| Jumping hedges on the strength of the Mellin transform | |
| E0778: R. Mamon | |
| A multivariate-index-driven anomaly detection system with supervised learning |
| Session EO349 | Room: 104 (Hybrid 4) |
| Recent advances in Bayesian computation and applications | Sunday 05.6.2022 16:50 - 18:30 |
| Chair: Minh-Ngoc Tran | Organizer: Minh-Ngoc Tran |
| E0481: T. Matsubara, J. Knoblauch, F.-X. Briol, C. Oates | |
| Robust generalised Bayesian inference for intractable likelihoods | |
| E0488: R. Loaiza-Maya, D. Frazier, G. Martin, B. Koo | |
| Loss-based variational Bayes prediction | |
| E0522: A. Thiery | |
| Creating manifold structures to accelerate MCMC sampling | |
| E0604: M.E. Khan | |
| The Bayesian learning rule |
| Session EO449 | Room: 105 (Hybrid 5) |
| Advances in productivity analysis and measurement (virtual) | Sunday 05.6.2022 16:50 - 18:30 |
| Chair: Artem Prokhorov | Organizer: Artem Prokhorov |
| E0435: H.-P. Lai | |
| Indirect inference of stochastic frontier models | |
| E0437: R. James, A. Prokhorov, P. Schmidt, C. Amsler | |
| Improving predictions of technical inefficiency | |
| E0471: M. Sokolov, A. Alekseev | |
| How to measure the average rate of change | |
| E1033: M. Mamonov, A. Prokhorov, C. Parmeter | |
| Assessing bank performance under volatile exchange rate |
| Session EO107 | Room: 106 (Hybrid 6) |
| High-dimensional inference and detection under dependence | Sunday 05.6.2022 16:50 - 18:30 |
| Chair: Ansgar Steland | Organizer: Ansgar Steland |
| E0304: J. Hirukawa, K. Fujimori | |
| Innovation algorithm of fractionally integrated processes and applications to the estimation of parameters | |
| E0237: F. Mies, A. Steland | |
| Sequential Gaussian approximation for nonstationary time series in high dimensions | |
| E0649: D. Loboda | |
| A Gaussian approximation result for weakly dependent random fields using dependency graphs | |
| E0788: M. Mboya, S. Wingert, P. Sibbertsen | |
| Distinguishing between breaks in the mean and breaks in persistence under long memory |
| Session EO197 | Room: Virtual R1 |
| Spatial models in economic research | Sunday 05.6.2022 16:50 - 18:30 |
| Chair: Pipat Wongsa-art | Organizer: Pipat Wongsa-art |
| E0329: T. Hoshino | |
| Estimating a continuous treatment model with spillovers: A control function approach | |
| E0417: P. Mossay | |
| Spatial economic models of social interactions | |
| E0724: P. Wongsa-art | |
| Analysis of functional data: From serial to spatial dependence | |
| E0808: F. Moscone, M. Billio, J. Madia, E. Tosetti | |
| The impact of COVID-19 on SMEs default: The role of the network |
| Session EO297 | Room: Virtual R2 |
| Theories and methodologies for stochastic processes | Sunday 05.6.2022 16:50 - 18:30 |
| Chair: Teppei Ogihara | Organizer: Teppei Ogihara |
| E0165: Y. Potiron | |
| Existence in the inverse Shiryaev problem | |
| E0230: T. Ogihara, Y. Uehara | |
| Local asymptotic normality for jump-diffusion processes | |
| E0457: S. Eguchi | |
| Model comparison for ergodic Levy driven SDEs in YUIMA | |
| E0739: S. Nakakita, M. Imaizumi | |
| Benign overfitting in stochastic regression |
| Session EO303 | Room: Virtual R3 |
| Bayesian econometrics for evidence-based policy making | Sunday 05.6.2022 16:50 - 18:30 |
| Chair: Thomas Zoerner | Organizer: Thomas Zoerner |
| E0646: T. Zoerner, F. Huber, N. Hauzenberger | |
| Hawks vs. Doves: Monetary policy effectiveness in light of diverging national policy stances | |
| E0705: N. Kuschnig | |
| Uncertain spillover effects and priors for spatial models | |
| E0783: G. Zens, M. Steel | |
| Accounting for model uncertainty in Bayesian Poisson regression models | |
| E0785: L. Vashold, J. Crespo Cuaresma | |
| Forecasting sectoral greenhouse gas emissions for a global sample |
| Session EO305 | Room: Virtual R4 |
| Climate econometrics | Sunday 05.6.2022 16:50 - 18:30 |
| Chair: Marina Friedrich | Organizer: Marina Friedrich |
| E0262: J. Zhou Lykke, M. Bennedsen, E. Hillebrand | |
| A state space representation of a two-component energy balance model | |
| E0356: F. Dorn, T. Kneib, S. Maxand | |
| The dependence between income inequality and carbon emissions: A distributional copula analysis | |
| E0381: M. Friedrich, Y. Lin | |
| Sieve Bootstrap inference for time-varying coefficient models | |
| E0562: F. Marotta | |
| Demand or supply: An empirical exploration of the effects of climate change on the macroeconomy |
| Session EO089 | Room: Virtual R6 |
| Recent advances in large panel data modelling | Sunday 05.6.2022 16:50 - 18:30 |
| Chair: Bin Peng | Organizer: Degui Li |
| Session EO171 | Room: Virtual R7 |
| Regression and bias reduction in extreme value theory | Sunday 05.6.2022 16:50 - 18:30 |
| Chair: Antoine Usseglio-Carleve | Organizer: Antoine Usseglio-Carleve |
| E0554: J. Hambuckers, M. Kratz, A. Usseglio-Carleve | |
| Automatic threshold selection for extreme value regression models | |
| E0648: J. El Methni, S. Girard, M. Allouche | |
| A refined Weissman estimator for extreme quantiles | |
| E0859: M. Bousebata, S. Girard, G. Enjolras | |
| Extreme partial least-squares | |
| E0893: Y. Abbas, A. Daouia, G. Stupfler | |
| Extremal expectile regression |
| Session EO239 | Room: Virtual R8 |
| Recent advances in big and complex data analysis | Sunday 05.6.2022 16:50 - 18:30 |
| Chair: Xiaojun Mao | Organizer: Xiaojun Mao |
| E0569: X. He | |
| Structure learning via unstructured kernel-based M-regression | |
| E0655: B. Gang | |
| Large-scale importance selection of heteroscedastic units | |
| E0693: Y. Hou | |
| A two-stage model for high-risk prediction in insurance ratemaking | |
| E0777: Z. Wang, X. Mao, J.K. Kim | |
| Functional calibration under non-probability survey sampling |
| Session EC434 | Room: 107 (Hybrid 7) |
| Contributions in applied statistics and econometrics | Sunday 05.6.2022 16:50 - 18:30 |
| Chair: Makoto Takahashi | Organizer: EcoSta |
| Parallel session K: EcoSta2022 | Monday 06.6.2022 | 07:40 - 09:20 |
| Session EO315 | Room: Virtual R1 |
| Recent developments on microbiome data analysis | Monday 06.6.2022 07:40 - 09:20 |
| Chair: Wodan Ling | Organizer: Gen Li |
| E0171: S. Jung, S. Lee, J. Ahn | |
| Resampling-based inferences for compositional regression when sample sizes are limited | |
| E0514: J. Fukuyama, L. Symul, K. Sankaran | |
| Multiscale analysis of count data through topic alignment | |
| E0720: D. Wu | |
| A Gaussian mixture model to integrate metagenome and metatranscriptome data | |
| E0811: K. Chen | |
| Scalable and interpretable rare feature aggregation with microbiome data |
| Session EO311 | Room: Virtual R10 |
| Modern statistical methods for longitudinal and survival data | Monday 06.6.2022 07:40 - 09:20 |
| Chair: Esra Kurum | Organizer: Esra Kurum |
| E0526: J. Dubin | |
| Challenges of modeling longitudinal intensive care unit data | |
| E0506: E.J.-C. Juarez-Colunga, P. Langner | |
| Efficiency loss with binary pre-processing of continuous monitoring data | |
| E0546: C. Wang | |
| Optimal cut-points for screening for pre-clinical disease based on various criteria | |
| E0532: E. Kurum | |
| A Bayesian multilevel time-varying framework for joint modeling of hospitalization and survival in patients on dialysis |
| Session EO121 | Room: Virtual R11 |
| Recent advances in models with complex dependence | Monday 06.6.2022 07:40 - 09:20 |
| Chair: Cheng Li | Organizer: Cheng Li |
| E0449: Y. Zhu, C. Li, D. Dunson | |
| Classification trees for imbalanced data: Surface-to-volume regularization | |
| E0575: S. Jiang, S. Tokdar | |
| Consistent Bayesian community detection for assortative networks | |
| E0732: D. Li, A. Jones, B. Engelhardt | |
| Probabilistic contrastive principal component analysis | |
| E0749: L. Lin | |
| Intrinsic and extrinsic deep learning on manifolds |
| Session EO163 | Room: Virtual R12 |
| Statistical machine learning with networks, matrices, and manifolds | Monday 06.6.2022 07:40 - 09:20 |
| Chair: Joshua Cape | Organizer: Joshua Cape |
| E0202: K. Levin | |
| Limit theorems for out-of-sample extensions of spectral graph embeddings | |
| E0663: A. Little | |
| Clustering and dimension reduction via Fermat distances | |
| E0702: C.M. Le, T. Li | |
| Network estimation by adaptive mixing | |
| E0741: J. Arroyo, C. Priebe, V. Lyzinski | |
| Graph matching between bipartite and unipartite networks |
| Session EO385 | Room: Virtual R13 |
| Dependency in network data | Monday 06.6.2022 07:40 - 09:20 |
| Chair: Moo K Chung | Organizer: Moo K Chung |
| E0298: S. Kaji | |
| Introduction to persistent homology for graph analysis | |
| E0982: A. Leow | |
| Modeling abnormal brain dynamics using statistical physics and MRI | |
| E0999: H. Ombao | |
| Spectral non-linear Granger causality for multivariate time series | |
| E1011: P.V. Redondo, R. Huser, H. Ombao | |
| Functional-coefficient models for multivariate time series in designed experiments: Applications to brain signals |
| Session EO033 | Room: Virtual R2 |
| New developments in design and analysis of experiments | Monday 06.6.2022 07:40 - 09:20 |
| Chair: John Stufken | Organizer: John Stufken |
| E0194: W. Mueller, A. Pazman, M. Hainy | |
| A convex approach to optimum design of experiments with correlated observations | |
| E0255: R. Singh, J. Stufken | |
| Design selection for 2-level supersaturated designs | |
| E0621: R.-B. Chen | |
| Particle swarm exchange algorithms with applications in generating optimal model-discrimination designs | |
| E0805: M. Kao | |
| Experimental designs for functional modeling of longitudinal data |
| Session EO119 | Room: Virtual R3 |
| Advances in Bayesian methods and computation | Monday 06.6.2022 07:40 - 09:20 |
| Chair: Jouchi Nakajima | Organizer: Jouchi Nakajima |
| E0198: N. Awaya, L. Ma | |
| Tree boosting for learning probability measures | |
| E0961: M. Xie, K.A. Aastveit, K. Irie, M. West | |
| Simultaneous graphical dynamic linear models for macroeconomic policy | |
| E0295: T. Ishihara | |
| A realized multi-factor regression using a multivariate stochastic volatility model | |
| E0256: M. Takahashi, Y. Omori, T. Watanabe, Y. Yamauchi | |
| Realized stochastic volatility models with skew-t distributions |
| Session EO101 | Room: Virtual R4 |
| Statistical modeling of challenging data | Monday 06.6.2022 07:40 - 09:20 |
| Chair: Yuedong Wang | Organizer: Yuedong Wang |
| Session EO129 | Room: Virtual R5 |
| Recent advances in machine learning | Monday 06.6.2022 07:40 - 09:20 |
| Chair: Yiming Ying | Organizer: Yiming Ying |
| E0364: H. Koehler, A. Christmann | |
| Total stability of SVMs and localized SVMs | |
| E0640: J. Fan | |
| Approximation of nonlinear functionals using deep ReLU networks | |
| E0672: Y. Lei | |
| Learning theory of stochastic gradient descent | |
| E0678: Y. Feng, Q. Wu | |
| A statistical learning assessment of Huber regression |
| Session EO131 | Room: Virtual R6 |
| Recent developments in dimension reduction and multivariate analysis | Monday 06.6.2022 07:40 - 09:20 |
| Chair: Yeonhee Park | Organizer: Yeonhee Park |
| E0797: S. Chakraborty, Z. Su | |
| A comprehensive Bayesian framework for envelope models | |
| E0827: M. Lee, S. Chakraborty, Z. Su | |
| A Bayesian approach to envelope quantile regression | |
| E0530: K. Lee | |
| Bayesian inference for multivariate probit model with latent envelope | |
| E0612: Z. Su, B. Li, D. Cook | |
| Envelope model for function-on-function linear regression |
| Session EO241 | Room: Virtual R7 |
| Estimation and inference of high dimensional time series | Monday 06.6.2022 07:40 - 09:20 |
| Chair: Danna Zhang | Organizer: Danna Zhang |
| Session EO207 | Room: Virtual R8 |
| Modern statistical methods for environmental data analysis | Monday 06.6.2022 07:40 - 09:20 |
| Chair: Whitney Huang | Organizer: Whitney Huang |
| E0478: L. Warr, M. Heaton, W. Christensen, P. White, S. Rupper | |
| Distributional validation of precipitation data products with spatially varying mixture models | |
| E0487: M. Bonas, S. Castruccio | |
| Calibration of spatio-temporal forecasts from urban air pollution data with sparse recurrent neural networks | |
| E0502: E. Murphy | |
| Joint modeling of wind speed and wind direction through a conditional approach | |
| E0559: L. Zhang | |
| Accounting for the spatial structure of weather systems in detected changes in precipitation extremes |
| Session EO275 | Room: Virtual R9 |
| Sequential analysis and online updating | Monday 06.6.2022 07:40 - 09:20 |
| Chair: Yan Zhuang | Organizer: Yan Zhuang |
| E0981: N. Mukhopadhyay | |
| Fixed-accuracy big data estimation of population Gini income inequality index: Practical distribution-free strategies | |
| E0217: D. Bhattacharjee, I. Silva, Y. Zhuang | |
| An adaptive Monte Carlo method to estimate confidence interval for population sizes under mark-recapture-mark sampling | |
| E0363: J. Wu | |
| Online updating of survival analysis | |
| E0427: S. Bapat | |
| Maximum precision estimation for a step-stress model using two-stage methodologies |
| Parallel session L: EcoSta2022 | Monday 06.6.2022 | 09:30 - 11:10 |
| Session EO085 | Room: Live Theater (Hybrid 2) |
| Variational inference in statistics and econometrics I | Monday 06.6.2022 09:30 - 11:10 |
| Chair: Pierre Alquier | Organizer: Pierre Alquier |
| E0494: R. Martin | |
| Gibbs posterior distributions: Construction, concentration, and calibration | |
| E0533: J.L. Montiel Olea | |
| On the robustness to misspecification of -posteriorsand their variational approximations | |
| E0988: A. Bhattacharya | |
| On statistical and algorithmic aspects of variational inference |
| Session EO261 | Room: Main Theater (Hybrid 1) |
| External validity and data fusion in causal inference (virtual) | Monday 06.6.2022 09:30 - 11:10 |
| Chair: Caleb Miles | Organizer: Caleb Miles |
| E0668: A. Buchanan, F. Li, S. Cole | |
| Generalizing trial evidence to target populations in non-nested designs: Applications to AIDS clinical trials | |
| E0942: I. Dahabreh | |
| Causally interpretable meta-analysis: Transporting inferences from multiple randomized trials to a target population | |
| E0735: K. Rudolph, I. Diaz | |
| Robust and efficient nonparametric estimation of transported total causal effects and mediation causal effects | |
| E0905: A. Luedtke | |
| Efficient estimation under data fusion |
| Session EO103 | Room: Virtual R1 |
| Recent developments in graphical models | Monday 06.6.2022 09:30 - 11:10 |
| Chair: Kuang-Yao Lee | Organizer: Kuang-Yao Lee |
| E0572: Z. Ren | |
| Simultaneous inference in multiple matrix-variate graphs for high-dimensional neural recordings | |
| E0971: A. Hudson | |
| Nonparametric assessment of conditional dependence using a restricted score test | |
| E0991: K.-Y. Lee, L. Li, B. Li | |
| Functional causal modeling via Karhunen-Loeve expansions | |
| E0995: K. Khare, P. Jalali, G. Michailidis | |
| A Bayesian subset specific approach to joint selection of multiple graphical models |
| Session EO075 | Room: Virtual R10 |
| Recent development in functional data analysis and cluster analysis | Monday 06.6.2022 09:30 - 11:10 |
| Chair: Guanqun Cao | Organizer: Yuhang Xu |
| Session EO047 | Room: Virtual R11 |
| Design and analysis of complex experiments: Theory and applications | Monday 06.6.2022 09:30 - 11:10 |
| Chair: MingHung Kao | Organizer: MingHung Kao |
| E0288: J. Stufken, Y. Shi, W. Yu | |
| Optimal designs for generalized linear mixed models | |
| E0755: A. Mandal | |
| Modeling and active learning for experiments with quantitative-sequence factors | |
| E0819: R. Pan | |
| Experimental design and active learning | |
| E0824: F.K.H. Phoa, Y.-H. Liao | |
| The summary of effect aliasing structure for supersaturated and factorial designs |
| Session EO193 | Room: Virtual R12 |
| Recent methods in finance | Monday 06.6.2022 09:30 - 11:10 |
| Chair: Soohun Kim | Organizer: Soohun Kim |
| E0333: S. Kim, D. Weagley, J. Kim | |
| The nature of ownership and stock returns | |
| E0528: A. Neuhierl, M. Weber, J. Freyberger, B. Hoeppner | |
| Missing data in asset pricing panels | |
| E0529: Y. Liao, A. Neuhierl, J. Fan, T. Ke | |
| Structural deep learning in conditional asset pricing | |
| E0701: G. Li, B. Han | |
| Idiosyncratic volatility and the consistency of the ICAPM |
| Session EO231 | Room: Virtual R13 |
| Recent advances in event history studies | Monday 06.6.2022 09:30 - 11:10 |
| Chair: Jianguo Sun | Organizer: Jianguo Sun |
| E0226: D. Sun | |
| A new robust approach for regression analysis of panel count data with time-varying covariates | |
| E0599: L. Chen, Y. Feng, J. Sun | |
| A class of additive transformation models for recurrent gap times | |
| E1032: Y. Guo, T. Tian, J. Sun | |
| High-dimensional variable selection for partially functional Cox regression with interval-censored data |
| Session EO211 | Room: Virtual R2 |
| Meta-analysis, network meta-analysis and IPD meta-analysis | Monday 06.6.2022 09:30 - 11:10 |
| Chair: Tiejun Tong | Organizer: Tiejun Tong |
| E0215: Y. Chen | |
| A robust and computational-efficient method for multiple-outcome network meta-analysis | |
| E0222: H. Chu, L. Siegel, H. Murad, R. Riley, F. Bazerbachi, Z. Wang | |
| A guide to estimating the reference range from a meta-analysis using aggregate or individual participant data | |
| E0639: J. Lim, M. Zhang, J. Barth, J. Lim, X. Wang | |
| Bayesian estimation and testing in random effect meta-analysis of rare binary adverse events with flexible variability | |
| E0213: J. Shi | |
| A unified framework for meta-analysis with the five-number summary |
| Session EO213 | Room: Virtual R3 |
| Recent advances in statistical modeling and computing for complex data | Monday 06.6.2022 09:30 - 11:10 |
| Chair: Weixin Yao | Organizer: Weixin Yao |
| E0518: X. Duan | |
| Two post-survey imaginary random mechanisms with implications | |
| E0865: R. Zhang, F. Sha | |
| Adversarially robust subspace learning in the spiked covariance model | |
| E0912: Y. Chen, Z. Lin, H.-G. Mueller | |
| Wasserstein regression | |
| E1045: H. Lyu | |
| Stochastic regularized block majorization-minimization with weakly convex and multi-convex surrogates | |
| E0916: S. Ghosh | |
| Exact permutation/randomization tests algorithms |
| Session EO355 | Room: Virtual R4 |
| New directions in high-dimensional and functional data analysis | Monday 06.6.2022 09:30 - 11:10 |
| Chair: Alexander Petersen | Organizer: Alexander Petersen |
| E0509: L. Xiao | |
| Functional data analysis for longitudinal data with informative observation times | |
| E0890: A. Petersen, W. Meiring, X. Liu, A. Ghosal | |
| Regression modeling for distributional response data | |
| E0686: C. Liu | |
| Low-rank latent matrix factor-analysis modeling for generalized linear regression with imaging biomarkers | |
| E0958: Y. Yang, H.L. Shang, Y. Gao | |
| Factor-augmented smoothing model for functional data |
| Session EO027 | Room: Virtual R5 |
| Recent advances in matrix and tensor learning | Monday 06.6.2022 09:30 - 11:10 |
| Chair: Kejun He | Organizer: Raymond Ka Wai Wong |
| E0206: B. Dai, X. Shen, W. Pan | |
| Two-level monotonic multistage recommender systems | |
| E0588: X. Tang | |
| Correlation tensor decomposition and its application in spatial imaging data | |
| E0593: R. Han, Y. Luo, M. Wang, A. Zhang | |
| Exact clustering in tensor block model: Statistical optimality and computational limit | |
| E0665: R.K.W. Wong, J. Wang, X. Mao, K.C.G. Chan | |
| Matrix completion with model-free weighting |
| Session EO415 | Room: Virtual R6 |
| Gaussian process regression models | Monday 06.6.2022 09:30 - 11:10 |
| Chair: Xia Wang | Organizer: Xia Wang |
| E0355: A. Halder, S. Mohammed, D. Dey | |
| Bayesian variable selection in double generalized linear Tweedie spatial process models | |
| E0715: Y.-B. Wang, W. Huang, Y.-M. Chung, J. Mandel, H.-T. Wu | |
| Airflow recovery using synchrosqueezing transform and locally stationary Gaussian process regression | |
| E0746: S. Song, A. Palipana, R. Szczesniak, N. Gupta | |
| Joint modeling with integrated fractional Brownian motion | |
| E0607: X. Wang, W. Su, R. Szczesniak | |
| Flexible link functions in a joint hierarchical Gaussian process model |
| Session EO371 | Room: Virtual R7 |
| Advances in statistical methods for handling complex data | Monday 06.6.2022 09:30 - 11:10 |
| Chair: MinJae Lee | Organizer: MinJae Lee |
| Session EO201 | Room: Virtual R8 |
| Statistical models \& machine learning for official statistics and surveys | Monday 06.6.2022 09:30 - 11:10 |
| Chair: Scott Holan | Organizer: Scott Holan |
| E0223: K. McConville | |
| Tackling the overabundance of options in survey estimation | |
| E0279: Y. Si | |
| On the use of auxiliary variables in multilevel regression and poststratification | |
| E0277: D. Toth, S. Holan, D. Bhaduri | |
| Design consistent Bayesian tree models | |
| E0287: S. Holan, R. Janicki, P. Parker | |
| Computationally efficient Bayesian unit-level models for non-Gaussian data under informative sampling |
| Session EO063 | Room: Virtual R9 |
| Modern statistical methods in data science | Monday 06.6.2022 09:30 - 11:10 |
| Chair: Yichuan Zhao | Organizer: Yichuan Zhao |
| E0661: W. Ning, S. Ratnasingam | |
| Confidence intervals of mean residual life function in length-biased sampling based on modified empirical likelihood | |
| E0855: F. Tan, H. Peng | |
| Optimal subsampling in a massive data linear regression | |
| E1039: M. Zhang | |
| Robust method for optimal treatment decision making based on survival data | |
| E0765: Y. Zhao, K. Alemdjrodo | |
| Novel empirical likelihood inference for the mean difference with right-censored data |
| Parallel session N: EcoSta2022 | Monday 06.6.2022 | 13:30 - 14:45 |
| Session EO301 | Room: Live Theater (Hybrid 2) |
| Variational inference in statistics and econometrics II | Monday 06.6.2022 13:30 - 14:45 |
| Chair: Pierre Alquier | Organizer: Pierre Alquier |
| E0536: M.-N. Tran, P. Tseng, R. Kohn | |
| Variational Bayes for models with nuisance parameters | |
| E0537: Y. Shapovalova | |
| Inference in stochastic volatility models with variational sequential Monte Carlo | |
| E1002: M. Magris, A. Iosifidis, M. Shabani | |
| Bayesian bilinear neural network for predicting the mid-price dynamics in limit-order book markets |
| Session EO387 | Room: Main Theater (Hybrid 1) |
| Discrimination and principal component analysis of signals | Monday 06.6.2022 13:30 - 14:45 |
| Chair: Yan Liu | Organizer: Yan Liu |
| E0243: Y. Goto, M. Taniguchi | |
| Discriminant analysis based on binary time series | |
| E0250: K. Fujimori, Y. Goto, Y. Liu | |
| Sparse principal component analysis for high-dimensional stationary time series | |
| E0768: K. Chen, C.Y. Yau, Y. Li | |
| Functional threshold autoregressive model |
| Session EO057 | Room: Virtual R1 |
| Innovative approaches in ordinal and mixed-type data modelling | Monday 06.6.2022 13:30 - 14:45 |
| Chair: Cristina Mollica | Organizer: Cristina Mollica |
| E0573: M. Manisera, P. Zuccolotto | |
| A mixture model for ordinal variables measured on semantic differential scales | |
| E0615: C. Cavicchia | |
| Convex clustering of mixed numerical and categorical data | |
| E0936: R. Giubilei, T. Padellini, P. Brutti | |
| Energy trees: Regression and classification with structured and mixed-type covariates |
| Session EO199 | Room: Virtual R2 |
| Advances in mathematical data science | Monday 06.6.2022 13:30 - 14:45 |
| Chair: Xin Guo | Organizer: Lei Shi, Xin Guo |
| E0538: P. Gensler, A. Christmann | |
| Robustness of kernel-based pairwise learning | |
| E0628: D. Xiang | |
| Error analysis of OWL algorithms with varying Gaussians and convex loss | |
| E0810: X. Chen | |
| Regularized Kaczmarz algorithm |
| Session EO227 | Room: Virtual R3 |
| Topics on high-dimensional and complex models | Monday 06.6.2022 13:30 - 14:45 |
| Chair: Eugen Pircalabelu | Organizer: Eugen Pircalabelu |
| E0263: I. Wilms, J. Bien | |
| Node aggregation in large-scale graphical models | |
| E0660: J. Zhou, G. Claeskens | |
| On variables selection Type-I and type-II error tradeoff for high dimensional logistic regression | |
| E0654: Y. Zhao | |
| Residual-based estimation of parametric copulas under regression |
| Session EO389 | Room: Virtual R4 |
| New frontiers in econometrics | Monday 06.6.2022 13:30 - 14:45 |
| Chair: Namhyun Kim | Organizer: Namhyun Kim |
| E0680: H. Chiang, Y. Matsushita, T. Otsu | |
| Multiway empirical likelihood | |
| E0924: N. Kim | |
| Varying coefficient model with correlated error components: Application to disparities between mental health services | |
| E0955: Y. Zu | |
| Comparing survey based forecasts |
| Session EO145 | Room: Virtual R5 |
| Recent development on change point detection | Monday 06.6.2022 13:30 - 14:45 |
| Chair: Weichi Wu | Organizer: Lixing Zhu |
| E0166: W. Zhao, L. Zhu | |
| Multiple change point detection for high-dimensional data | |
| E0331: W. Wu, Z. Zhou | |
| Multiscale jump testing and estimation under complex temporal dynamics | |
| E0830: J. Huang, J. Wang, L. Zhu | |
| An adaptive-to-change ridge-ratio criterion for multiple change points in high-dimensional tensors |
| Session EO079 | Room: Virtual R6 |
| Recent statistical analysis of microbiome data | Monday 06.6.2022 13:30 - 14:45 |
| Chair: Sangwook Kang | Organizer: Taesung Park |
| E1022: T. Park, N. Kang, H. Koh | |
| Association test for longitudinal microbiome data | |
| E1035: Y. Chung | |
| Using taxonomic ranks improves the prediction of case-control analysis of microbiome data | |
| E1029: S. Won | |
| Phylogenetic tree-based microbiome association test |
| Session EO135 | Room: Virtual R7 |
| Advances in time series, random forests and causal inference | Monday 06.6.2022 13:30 - 14:45 |
| Chair: Hiroshi Shiraishi | Organizer: Hiroshi Shiraishi |
| E0560: H. Shiraishi, T. Nakamura | |
| Generalized random forests for dependent data | |
| E0650: T. Nakamura, H. Shiraishi | |
| Causal trees and forest with sufficient dimension reduction | |
| E0170: E. Scornet | |
| Study of a well-known importance measure computed via decision trees |
| Session EP001 | Room: Poster Room |
| Poster session (only virtual) | Monday 06.6.2022 13:30 - 14:45 |
| Chair: Cristian Gatu | Organizer: EcoSta |
| E0445: M. Cai | |
| Graphical and numerical diagnostic tools to assess multiple imputation models by posterior predictive checking | |
| E0556: S. MaraBeh, E. Mahdi | |
| Variogram modeling for spatial correlation in structural MRI images | |
| E0832: H. Lim, A.K.H. Kim | |
| Matching quantiles estimation for discrete distribution | |
| E1023: M. Ahmadi, C. Casoli, M. Manera, D. Valenti | |
| The effect of climate change on economic growth: A structural global vector autoregressive approach |
| Parallel session O: EcoSta2022 | Monday 06.6.2022 | 15:15 - 16:55 |
| Session EO321 | Room: Live Theater (Hybrid 2) |
| Advancements in Bayesian mixture models | Monday 06.6.2022 15:15 - 16:55 |
| Chair: Raffaele Argiento | Organizer: Andrea Cremaschi |
| E0181: B. Franzolini, A. Lijoi, I. Pruenster | |
| Model selection for maternal hypertensive disorders with symmetric hierarchical Dirichlet processes | |
| E0273: G. Malsiner-Walli, S. Fruhwirth-Schnatter, B. Gruen | |
| Mixtures of finite mixtures and the telescoping sampler | |
| E0851: T. Rigon, A. Zito, D. Dunson | |
| Learning the number of clusters: Conjugate prior for the Dirichlet process precision parameter | |
| E1003: R. Argiento, L. Paci, E. Filippi-Mazzola | |
| Clustering categorical data via Hammingd istance |
| Session EO323 | Room: Main Theater (Hybrid 1) |
| Monetary and fiscal policies in DSGE models | Monday 06.6.2022 15:15 - 16:55 |
| Chair: Takeki Sunakawa | Organizer: Takeki Sunakawa |
| E0211: T. Sunakawa, M. Katagiri | |
| Forward guidance as a monetary policy rule | |
| E0212: M. Katagiri | |
| Systematic foreign exchange intervention and macroeconomic stability: A Bayesian DSGE approach | |
| E0214: K. Hasui, S. Hoshino | |
| Habit persistence and zero lower bound risk under optimal discretionary policy | |
| E0450: H. Morita, F. Zanetti, L. Melosi | |
| The signalling effects of fiscal announcements |
| Session EO175 | Room: Virtual R1 |
| Compositional data analysis | Monday 06.6.2022 15:15 - 16:55 |
| Chair: Christine Thomas-Agnan | Organizer: Christine Thomas-Agnan |
| E0512: J. Saperas Riera, J.A. Martin-Fernandez | |
| Contributions of the compositional data methodology to constrained optimization in economics | |
| E0659: T.H. Trinh | |
| Climate change and rice yield: Compositional scalar-on-function regression approach | |
| E0750: C. Thomas-Agnan, A. Ruiz-Gazen, T. Laurent, C. Mondon | |
| Detecting outliers in compositional data using invariant coordinate selection | |
| E0763: T. Yoshida, D. Murakami, H. Seya | |
| Location powered quotient: A compositional data analysis-based approach |
| Session EO025 | Room: Virtual R2 |
| Innovative technologies for big data | Monday 06.6.2022 15:15 - 16:55 |
| Chair: Philip Yu | Organizer: Philip Yu |
| E0630: K.H. Ho, T.-T. Chan, P. Yu | |
| Return correlation and volatility spillover among NFT, NFT-related coin, and cryptocurrency markets | |
| E0696: Z. Zhu, K. Zhu, D. Li, X. Yang | |
| A distributional perspective on autoencoder asset pricing models | |
| E0327: X. Wang, P. Yu, W. Yang, J. Su | |
| Bayesian robust tensor completion via CP decomposition | |
| E0596: P. Yu, Y. Zhuang | |
| Preference learning across social networks for recommendations |
| Session EO263 | Room: Virtual R3 |
| Bayesian modeling in social sciences | Monday 06.6.2022 15:15 - 16:55 |
| Chair: Kazuhiko Kakamu | Organizer: Kazuhiko Kakamu |
| E0690: K. Kakamu | |
| Bayesian dynamic modeling of Gini coefficient from grouped data | |
| E0901: Y. Kawakubo, G. Kobayashi | |
| Estimation of area-wise income distributions based on household-level grouped data | |
| E0525: G. Kobayashi, S. Sugasawa, Y. Kawakubo | |
| Spatio-temporal smoothing, interpolation and prediction of income distributions based on grouped data | |
| E0534: S. Sugasawa, D. Cabel, M. Kato, K. McAlinn, K. Takanashi | |
| Spatially-varying bayesian predictive synthesis for flexible and interpretable spatial prediction |
| Session EO105 | Room: Virtual R4 |
| Recent advances of time series analysis | Monday 06.6.2022 15:15 - 16:55 |
| Chair: Wai-keung Li | Organizer: Wai-keung Li |
| E0359: F. Huang, Y. Zheng, K. Lu, G. Li | |
| SARMA: A computationally scalable high-dimensional time series model | |
| E0586: K. Song | |
| Estimation based on martingale difference divergence with insufficient instrumental variables | |
| E0629: M. Li | |
| Bootstrapping robust goodness-of-fit tests for GARCH models | |
| E0645: W.-K. Li | |
| Testing and modelling for the structural change in covariance matrix time series with multiplicative form |
| Session EO123 | Room: Virtual R5 |
| Recent advances in applied probability and statistics | Monday 06.6.2022 15:15 - 16:55 |
| Chair: Li-Hsien Sun | Organizer: Li-Hsien Sun |
| E0197: W. Huang, Z. Zhang | |
| Nonparametric estimation of the continuous treatment effect with measurement error | |
| E0409: C.-L. Kao, V. Tseng, Y.-S. Chen | |
| Extracting stock predictive information in fund managers decisions through machine learning with hypergraph | |
| E0762: L. Huang, Z. Zhang | |
| Nonparametric estimation of general mediation effects by calibration weighting | |
| E0882: C. Chang | |
| Estimation for multiple-threshold regression models |
| Session EO379 | Room: Virtual R6 |
| High dimensional statistical analysis and applications | Monday 06.6.2022 15:15 - 16:55 |
| Chair: Su-Yun Huang | Organizer: Su-Yun Huang |
| E0441: H.H.-S. Lu | |
| Statistical learning for AI assisted clinics | |
| E0176: H. Hung | |
| A generalized information criterion for high-dimensional PCA rank selection | |
| E0168: S.-H. Wang, S.-Y. Huang | |
| Perturbation theory for cross data matrix-based PCA | |
| E0472: S.-C. Chung | |
| Contrastive modeling for Cryo-EM 3D orientation estimations |