KEYNOTE TALKS (GMT+8)
| Opening and keynote talk 1 | Thursday 24.6.2021 | 08:00 - 09:00 | Room: R01 |
| Testing for time stochastic dominance | |||
| Speaker: Y.-J. Whang | Chair: Mike So | ||
| Keynote talk 2 | Saturday 26.6.2021 | 12:55 - 13:45 | Room: R01 |
| Joint modeling of complex data with latent variables | |||
| Speaker: X. Song | Chair: Ana Colubi | ||
| Closing and keynote talk 3 | Saturday 26.6.2021 | 17:35 - 18:30 | Room: R01 |
| Robust and consistent variable selection in high-dimensional generalized linear models | |||
| Speaker: E. Ronchetti Co-authors: M. Avella-Medina | Chair: Erricos Kontoghiorghes | ||
PARALLEL SESSIONS (GMT+8)
| Parallel session B: EcoSta2021 | Thursday 24.6.2021 | 09:10 - 10:25 |
| Session EO287 | Room: R01 |
| Advanced inferential tools for modern data | Thursday 24.6.2021 09:10 - 10:25 |
| Chair: Daoji Li | Organizer: Shujie Ma |
| Session EO133 | Room: R02 |
| Novel developments in low-rank modeling | Thursday 24.6.2021 09:10 - 10:25 |
| Chair: Raymond Ka Wai Wong | Organizer: Raymond Ka Wai Wong |
| E0201: E. Chi | |
| A scalable algorithm for estimating a low-rank plus sparse matrix | |
| E0330: X. Mao | |
| Robust reduced rank regression in a distributed setting | |
| E0509: J. Kang, B. Wu, Y. Guo | |
| Bayesian spatial blind source separation via the thresholded Gaussian process |
| Session EO017 | Room: R03 |
| Emerging development in the analysis of censored data | Thursday 24.6.2021 09:10 - 10:25 |
| Chair: Wenqing He | Organizer: Wenqing He |
| E0417: Y.-H. Choi, S. Lee, L. Briollais | |
| Modeling time-dependent effects of covariates in the analysis of time-to-event data arising from family-based studies | |
| E0638: G. Yi | |
| Semiparametric methods for left-truncated and right-censored survival data with covariate measurement error | |
| E0669: Y. Peng, P.-S. Shen, H.-J. Chen, C.-M. Chen | |
| Length-biased and interval-censored data with a nonsusceptible fraction |
| Session EO181 | Room: R04 |
| Developments in Markov Chain theory and methodology | Thursday 24.6.2021 09:10 - 10:25 |
| Chair: James Flegal | Organizer: James Flegal |
| E0172: J. Park, I.H. Jin | |
| Bayesian model selection for ultrahigh-dimensional doubly-intractable distributions | |
| E0230: D. Vats, J. Flegal | |
| Lugsail lag windows and their application to MCMC | |
| E0574: J. Flegal, D. Vats, G. Jones, N. Robertson | |
| Visualizing simultaneous uncertainty in Monte Carlo experiments |
| Session EO161 | Room: R05 |
| Recent advances in statistical learning | Thursday 24.6.2021 09:10 - 10:25 |
| Chair: Paromita Dubey | Organizer: Gourab Mukherjee |
| E0209: I.-Y. Kwak | |
| Detecting voice spoofing attacks with residual network and max filter map with Grad-CAM activation | |
| E0503: L. Zhang | |
| The cost of privacy in generalized linear models: Algorithms and minimax lower bounds | |
| E0558: P. Dubey, H.-G. Mueller | |
| Functional models for time varying random objects |
| Session EO033 | Room: R06 |
| Novel statistical modeling and computing methods for complex data | Thursday 24.6.2021 09:10 - 10:25 |
| Chair: Tsung-I Lin | Organizer: Tsung-I Lin |
| E0476: H. Abe | |
| A Bayesian nonparametric approach to inference for orthogonal nonnegative matrix factorization | |
| E0199: W.-L. Wang | |
| Mixtures of multivariate t nonlinear mixed models for multiple longitudinal data with heterogeneity and missingness | |
| E0500: F. Schumacher, V.H. Lachos Davila, L. Avila Matos | |
| Scale mixture of skew-normal linear mixed models with within-subject serial dependence |
| Session EO221 | Room: R07 |
| Recent advances in multivariate and high-dimensional time series | Thursday 24.6.2021 09:10 - 10:25 |
| Chair: Sayar Karmakar | Organizer: Sayar Karmakar |
| E0609: S. Karmakar | |
| Simultaneous prediction intervals for high-dimensional vector autoregression | |
| E0716: S. Deb, S. Karmakar | |
| A new clustering approach for spatio-temporal data | |
| E0305: A. Roy | |
| Bayesian time-aligned factor analysis of paired multivariate time series |
| Session EO205 | Room: R08 |
| Nonparametric and semiparametric methods | Thursday 24.6.2021 09:10 - 10:25 |
| Chair: Yuedong Wang | Organizer: Yuedong Wang |
| E0226: Y. Wang | |
| Low rank approximation for smoothing splinevia eigensystem truncation | |
| E0436: J. Yu, Y. Wang, A. Liu, J. Shi | |
| Joint asymptotics for smoothing spline semiparametric nonlinear models | |
| E0488: P. Ma | |
| Statistical computing meets quantum computing |
| Parallel session C: EcoSta2021 | Thursday 24.6.2021 | 10:35 - 12:15 |
| Session EO255 | Room: R01 |
| Statistical methods of causal inference | Thursday 24.6.2021 10:35 - 12:15 |
| Chair: Yen-Tsung Huang | Organizer: Yen-Tsung Huang |
| E0258: J.-C. Yu, Y.-T. Huang | |
| A novel approach to semi-competing risks with left truncation via causal mediation modeling | |
| E0365: Y.-T. Huang | |
| Causal mediation of disease natural history | |
| E0372: Y. Zhao, L. Li, B. Caffo | |
| Multimodal neuroimaging data integration and pathway analysis | |
| E0195: S.-H. Lin | |
| Generalized interventional approach for causal mediation analysis with causally ordered multiple mediators |
| Session EO219 | Room: R02 |
| Causal inference and large-scale data analysis | Thursday 24.6.2021 10:35 - 12:15 |
| Chair: Daoji Li | Organizer: Daoji Li |
| Session EO189 | Room: R03 |
| Recent advances in statistical methods for complex biomedical data | Thursday 24.6.2021 10:35 - 12:15 |
| Chair: Yingwei Peng | Organizer: Yingwei Peng |
| E0302: Y. Niu, Y. Peng, H. Liang, X. Wang | |
| Improving marginal hazard ratio estimation using quadratic inference functions | |
| E0525: Y. Zhu, X. Cai, Y. Huang | |
| Causal mediation analysis based on partial linear models | |
| E0639: W. He | |
| Support vector machine with graphical network structures in features | |
| E0661: P. Li | |
| A comparison between GBM and the Cox PH approaches with a focus on the R-packages GBM and survival |
| Session EO241 | Room: R04 |
| Bayesian modeling in biostatistics | Thursday 24.6.2021 10:35 - 12:15 |
| Chair: Michele Guindani | Organizer: Michele Guindani |
| E0237: M.J. Ha, F. Stingo, V. Baladandayuthapani, J. Long | |
| Integrative graphical modeling and network mediation analysis | |
| E0736: F. Denti | |
| Horseshoe pit: A unified framework for large-scale Bayesian inference | |
| E0155: M. Guindani, F. Denti, F. Camerlenghi, A. Mira | |
| A common atom model for the Bayesian nonparametric analysis of nested data |
| Session EO123 | Room: R05 |
| Hybrid statistical approach for complex data | Thursday 24.6.2021 10:35 - 12:15 |
| Chair: Wenyu Gao | Organizer: Inyoung Kim |
| E0163: T. Tong | |
| Fixed-effects model: The most convincing model for meta-analysis with few studies | |
| E0216: M. Song | |
| Performing genetic association tests in arbitrarily structured populations | |
| E0741: L. Shan | |
| Using an estimated sparse two level gene pathway network for QDA to predict breast cancer patients treatment responses | |
| E0749: W. Gao, I. Kim, W. Nam, W. Zhou | |
| Nonparametric Bayesian functional clustering for breast cancer disparities |
| Session EO069 | Room: R06 |
| Design and analysis of complex experiments: Theory and applications | Thursday 24.6.2021 10:35 - 12:15 |
| Chair: MingHung Kao | Organizer: MingHung Kao |
| E0615: J. Stufken, R. Singh | |
| Factor selection in screening experiments | |
| E0707: S. Mandal | |
| A general approach for constrained optimal design | |
| E0650: W. Zheng | |
| Fast approximation of the Shapley values | |
| E0653: M. Kao | |
| Optimal designs for mixed continuous and binary responses with quantitative and qualitative factors |
| Session EC378 | Room: R07 |
| Contributions in methodological econometrics | Thursday 24.6.2021 10:35 - 12:15 |
| Chair: Christopher Parmeter | Organizer: EcoSta |
| E0695: S. Banafti | |
| Inferential theory for granular instrumental variables in high dimensions | |
| E0469: C. Parmeter, J. Racine, P. Du | |
| Shape constrained kernel PDF and PMF estimation | |
| E0493: J. Choi, H. Kwon | |
| Inference using nuclear-norm penalized estimator and its applications | |
| E0331: D. Seong | |
| Binary response model with many weak instrumental variables |
| Session EC343 | Room: R08 |
| Contributions in financial econometrics I | Thursday 24.6.2021 10:35 - 12:15 |
| Chair: Ke Zhu | Organizer: EcoSta |
| E0613: A. Sarantsev | |
| A new valuation measure for the stock market | |
| E0591: E. Hansen | |
| Predicting gold risk premium using machine learning methods | |
| E0202: X. Yao, M. Izzeldin, Z. Li | |
| Return predictability from variance differences: A fractionally co-integrated analysis | |
| E0723: A. Atak | |
| Reflexivity analysis of cryptocurrencies with a time-varying semi-parametric Hawkes process |
| Parallel session D: EcoSta2021 | Thursday 24.6.2021 | 13:15 - 15:20 |
| Session EO370 | Room: R01 |
| Trends and developments in regularization and shrinkage | Thursday 24.6.2021 13:15 - 15:20 |
| Chair: Keisuke Yano | Organizer: Keisuke Yano |
| E0287: K. Nakamura, K. Yano, F. Komaki | |
| Modeling the missing mechanism in partially ranked data with adjacency-based regularization | |
| E0418: H. Oda, F. Komaki | |
| Shrinkage priors on complex-valued Gaussian processes | |
| E0466: T. Matsuda, W. Strawderman | |
| Estimation under matrix quadratic loss and matrix superharmonicity | |
| E0675: Y. Hirose, R. Hasegawa, H. Imai | |
| An information-geometric method for parameter estimation on moving-average models | |
| E0694: Y. Choi, H. Cho, H. Son | |
| Capturing network effect via fused lasso penalty with application on shared-bike data |
| Session EO376 | Room: R03 |
| Statistical methods in phylogeny, population genetics and covid research | Thursday 24.6.2021 13:15 - 15:20 |
| Chair: Andreas Futschik | Organizer: Andreas Futschik |
| E0576: C. Kosiol, R. Borges | |
| Polymorphism-aware phylogenetic models for species tree inference | |
| E0626: M. Pelizzola | |
| Multiple haplotype reconstruction from allele frequency data | |
| E0651: R. Dutta, L. Pacchiardi, S. Gomes, D. Kalise | |
| Using mobility data in the design of optimal lockdown strategies for the COVID-19 pandemic | |
| E0684: A. Futschik | |
| Estimation of the largest mean Gaussian mixture component with population genetic applications | |
| E0708: M. Stehlik | |
| REDACS: Regional emergency driven adaptive cluster sampling for effective COVID-19 prevalence |
| Session EO131 | Room: R04 |
| Advances in extremal M-quantile regression | Thursday 24.6.2021 13:15 - 15:20 |
| Chair: Abdelaati Daouia | Organizer: Abdelaati Daouia |
| E0480: G. Stupfler, A. Daouia, I. Gijbels | |
| Extremiles: A new perspective on asymmetric least squares | |
| E0474: A. Daouia, G. Stupfler, I. Gijbels | |
| Extremile regression | |
| E0750: S. Padoan, G. Stupfler | |
| A unified approach for the estimation of some important risk measures | |
| E0471: A. Usseglio-Carleve, G. Stupfler, S. Girard | |
| Extreme conditional expectile estimation in heavy-tailed heteroscedastic regression models | |
| E0475: Y. Abbas, A. Daouia, G. Stupfler | |
| Extremal expectile regression |
| Session EO354 | Room: R05 |
| Trends and innovations in financial modelling | Thursday 24.6.2021 13:15 - 15:20 |
| Chair: Rogemar Mamon | Organizer: Rogemar Mamon |
| E0375: H. Xiong, R. Mamon, Y. Zhao | |
| The valuation of a guaranteed minimum maturity benefit under a regime-switching framework | |
| E0407: C. Erlwein-Sayer, S. Grimm | |
| Embedding regime-switching in modelling of credit spreads through neural networks | |
| E0623: X. Yu, Y.-J. Huang | |
| Time inconsistent optimal stopping under model ambiguity and financial applications | |
| E0630: S. Guo | |
| Adaptive online portfolio selection with transaction costs | |
| E0655: M. Rodrigo | |
| Calibrating with a smile the Mellin transform way |
| Session EO281 | Room: R06 |
| Recent advances in applied probability and statistics | Thursday 24.6.2021 13:15 - 15:20 |
| Chair: Li-Hsien Sun | Organizer: Li-Hsien Sun |
| E0532: C. Chang | |
| Detection of threshold points in mean and variance forthreshold regression models | |
| E0573: B. Zhang, H. Sang, H. Huang | |
| Bayesian clustering of spatial functional data based on random spanning trees | |
| E0578: Z. Zhang, O. Linton | |
| A unified framework for specification tests of continuous treatment effect models | |
| E0619: S. He | |
| Randomized algorithms for functional data analysis | |
| E0612: L.-H. Sun | |
| Mean-field games with heterogeneous groups: Application to banking systems | |
| E0757: W. Huang, A. Delaigle, P. Hall, A. Kneip | |
| Estimating the covariance of fragmented and other related types of functional data |
| Session EO053 | Room: R08 |
| Advances in financial time series analysis | Thursday 24.6.2021 13:15 - 15:20 |
| Chair: Toshiaki Watanabe | Organizer: Toshiaki Watanabe |
| E0617: M. So | |
| Bayesian inference of temporal trends in daily financial news | |
| E0310: K. Hatakenaka, K. Oya | |
| Bayesian analysis of price discovery on time-varying partial adjustment model | |
| E0314: M. Takahashi, T. Hayashi | |
| On the evaluation of intraday market quality in the limit-order book markets: A collaborative filtering approach | |
| E0326: M. Ubukata | |
| A time-varying jump tail risk measure using high-frequency options data | |
| E0526: J. Nakajima, T. Watanabe | |
| Stochastic volatility models with time-varying leverage effect |
| Session EC341 | Room: R02 |
| Contributions in time series | Thursday 24.6.2021 13:15 - 15:20 |
| Chair: Matthieu Marbac | Organizer: EcoSta |
| E0485: M. du Roy de Chaumaray, V. Patilea, M. Marbac | |
| Wilks theorem for semiparametric regressions with weakly dependent data | |
| E0721: F. Mies | |
| Functional estimation and change detection for nonstationary time series | |
| E0223: A. Rohmawati | |
| Modified upper prediction limit of vector autoregressive model: the case for estimating value-at-risk | |
| E0711: G. Romano, I. Eckley, P. Fearnhead, G. Rigaill | |
| FOCuS: Online changepoint detection with a constant per-iteration computational cost | |
| E0691: D. Yamazaki | |
| A modified sequential procedure to estimate the number of breaks in trend |
| Session EC345 | Room: R07 |
| Contributions in high dimensional and complex data analysis | Thursday 24.6.2021 13:15 - 15:20 |
| Chair: Chi Tim Ng | Organizer: EcoSta |
| E0606: M.A. Kaygusuz, V. Purutcuoglu | |
| A conditional randomization test for generalized additive models with bootstrap methods | |
| E0683: T. Nishiyama, M. Hyodo, H. Hayashi | |
| On the multiple comparison procedures among mean vectors for high-dimensional data under covariance heterogeneity | |
| E0548: M. Sauvenier | |
| Directional estimation in $l_0$ constrained regression | |
| E0588: J. Rydlewski | |
| Outlyingness-oriented causality | |
| E0563: S. Park, E. Ceulemans, K. Van Deun | |
| Sparse common and distinctive covariates logistic regression: Classification method for high-dimensional multiblock data |
| Session EP001 | Room: Poster |
| Poster Session | Thursday 24.6.2021 13:15 - 15:20 |
| Chair: Gil Gonzalez-Rodriguez | Organizer: EcoSta |
| E0266: S. Lee, Y. Cho, D. Yu | |
| Short-term forecasting for Korean coastal sea surface temperature and monitoring its levels | |
| E0460: G. Hacheme | |
| Machine learning and big data in econometrics: A machine learning-based specification test | |
| E0678: S. Cho, I. Hwang, K. Lee | |
| Exact inference for an exponential parameter under generalized progressive type II hybrid censored competing risk data | |
| E0679: K. Lee, Y. Seong, H. Koo | |
| Estimation of the Weibull distribution based on generalized adaptive progressive hybrid censored competing risks data | |
| E0732: J.F. Munoz-Elguezabal, J.D. Sanchez-Torres | |
| T-fold sequential-validation technique for out-of-distribution generalization with financial time series data |
| Parallel session E: EcoSta2021 | Thursday 24.6.2021 | 15:30 - 16:45 |
| Session EI007 | Room: R07 |
| Recent advancements on the analysis of panel data | Thursday 24.6.2021 15:30 - 16:45 |
| Chair: Tomohiro Ando | Organizer: Tomohiro Ando |
| E0156: R. Okui, W. Wang, R. Lumsdaine | |
| Estimation of panel group structure models with structural breaks in group memberships and coefficients | |
| E0191: T. Yamagata, G. Cui, M. Norkute, V. Sarafidis | |
| Two-step instrumental variable estimation of linear panel data models with interactive effects |
| Session EO247 | Room: R01 |
| Recent development in high-dimensional statistics | Thursday 24.6.2021 15:30 - 16:45 |
| Chair: Lizhu Tao | Organizer: Chenlei Leng |
| E0327: J. Austin, J.Q. Shi, R. Henderson | |
| Principal components analysis of correlated functional data | |
| E0399: B. Jiang | |
| Linear discriminant analysis with high dimensional mixed variables | |
| E0461: L. Tao, Y. She, C. Leng | |
| A sparse Ising model with latent variables |
| Session EO079 | Room: R03 |
| Nonparametric or default Bayesian methods with applications in medicine | Thursday 24.6.2021 15:30 - 16:45 |
| Chair: Yisheng Li | Organizer: Yisheng Li |
| E0575: S. Morita, P. Mueller, H. Abe | |
| Bayesian population finding in a randomized clinical trial | |
| E0521: S. Wade | |
| Bayesian scalar-on-image regression for automatically detected of regions of interest | |
| E0511: Y. Li, K. Lekdee, C. Yang, L. Ingsrisawang | |
| A uniform shrinkage prior in spatiotemporal Poisson models for count data |
| Session EO013 | Room: R04 |
| Recent advances in Bayesian inference I | Thursday 24.6.2021 15:30 - 16:45 |
| Chair: Igor Pruenster | Organizer: Igor Pruenster |
| E0387: J. Lee | |
| Post-processed posteriors for structured covariances | |
| E0492: S. Agapiou, M. Dashti, T. Helin | |
| Gauss versus Laplace rates of contraction under Besov regularity | |
| E0483: M. Catalano, A. Lijoi, I. Pruenster | |
| Measuring dependence in the Wasserstein distance for Bayesian nonparametric models |
| Session EO257 | Room: R05 |
| Modelling economic and financial time series: Estimation and forecasting | Thursday 24.6.2021 15:30 - 16:45 |
| Chair: Seok Young Hong | Organizer: Degui Li |
| E0303: T. Cheng, B. Zhao | |
| Stock return prediction: Stacking a variety of models | |
| E0320: W. Yao, L. Winkelmann | |
| Cojump anchoring | |
| E0350: S.Y. Hong, X. Zhao, O. Linton | |
| Separate noise and jumps from tick data: An endogenous thresholding approach |
| Session EO307 | Room: R06 |
| Bayesian analysis of business analytics problems | Thursday 24.6.2021 15:30 - 16:45 |
| Chair: Mike So | Organizer: Mike So |
| E0592: Y. Omori, A. Chu, M. So, H.-Y. So | |
| Multivariate randomized response for binary and ordinal data | |
| E0392: T. Watanabe, J. Nakajima | |
| High-frequency realized stochastic volatility model | |
| E0600: S.H. Chan | |
| Structural learning in Bayesian networks and business applications |
| Session EO185 | Room: R08 |
| Econometrics with applications to cryptocurrencies and the blockchain | Thursday 24.6.2021 15:30 - 16:45 |
| Chair: Jeffrey Chu | Organizer: Stephen Chan, Jeffrey Chu |
| E0537: P. Katsiampa, K. Gkillas, F. Longin | |
| Cryptocurrency market activity during extremely volatile periods | |
| E0712: S. Chan, J. Chu, Y. Zhang | |
| Bitcoin versus high-performance technology stocks in diversifying against global stock market indices | |
| E0722: J. Chu | |
| The maturity of crypto markets: A market efficiency test based on trading strategies |
| Session EG330 | Room: R02 |
| Contributions to statistical modelling | Thursday 24.6.2021 15:30 - 16:45 |
| Chair: Gilles Stupfler | Organizer: EcoSta |
| E0659: M. Matterne, I. Gijbels | |
| The average conditional and partial Kendall's tau | |
| E0662: A. McInerney, K. Burke | |
| Information-criteria-based model selection for neural networks | |
| E0690: M. ONeill, J. Gleeson, K. Burke | |
| Smooth BIC variable selection procedure for heteroscedastic data |
| Parallel session F: EcoSta2021 | Thursday 24.6.2021 | 16:55 - 18:35 |
| Session EI005 | Room: R06 |
| Advances in financial technology and risk analytics | Thursday 24.6.2021 16:55 - 18:35 |
| Chair: Mike So | Organizer: Mike So |
| E0467: W.-S. Chan | |
| Financing long-term care risks in a super-ageing society: A discrete choice experiment in Hong Kong | |
| E0596: P. Yu, R. Lu, X. Wang | |
| Sparse vector error correction models with application to cointegration-based trading | |
| E0602: G. Zhang, Y. Chen, Z. Wang, C. Zhou | |
| Optimal liquidation with hidden orders under self-exciting market order dynamics |
| Session EO259 | Room: R01 |
| Time series extremes: Modeling and forecasting | Thursday 24.6.2021 16:55 - 18:35 |
| Chair: Raphael Huser | Organizer: Raphael Huser |
| E0321: P. Krupskiy, M. Genton, R. Huser | |
| Copula models for time series extremes | |
| E0359: Y. Gong, R. Huser | |
| Asymmetric tail dependence modeling, with application to cryptocurrency market data | |
| E0432: J. Lee, M. de Carvalho, A. Rua | |
| Bayesian modeling of time-varying extremal dependence in international stock markets | |
| E0490: H. Kaibuchi, G. Stupfler, Y. Kawasaki | |
| A bias-reduced approach for dynamic estimation of extreme risk measures in financial time series |
| Session EO021 | Room: R02 |
| Multivariate distributions: Asymmetry, quantiles and more | Thursday 24.6.2021 16:55 - 18:35 |
| Chair: Anneleen Verhasselt | Organizer: Anneleen Verhasselt |
| E0643: J. Baillien, I. Gijbels, A. Verhasselt | |
| Inference for copulas with two-piece margins | |
| E0633: C. Ley, M. Hallin, S. Babic, L. Gelbgras | |
| Optimal tests for elliptical symmetry: Specified and unspecified location | |
| E0644: C. Adam, I. Gijbels | |
| Partially linear expectile regression using local polynomial fitting | |
| E0632: A. Verhasselt | |
| Quantile regression for longitudinal data via the multivariate generalized hyperbolic distribution |
| Session EO279 | Room: R03 |
| Innovative survival modelling approaches for various time-to-event data | Thursday 24.6.2021 16:55 - 18:35 |
| Chair: Il Do Ha | Organizer: Il Do Ha |
| E0252: K. Burke | |
| Semi-parametric multi-parameter regression survival modelling | |
| E0284: L. Xiang | |
| Quantile regression analysis of survival data with covariates subject to detection limits | |
| E0396: S. Kwon | |
| Semi-parametric copula survival models for clustered time-to-event data | |
| E0494: B. Seo, I.D. Ha | |
| A semiparametric AFT random-effect model |
| Session EO015 | Room: R04 |
| Recent advances in Bayesian Inference II | Thursday 24.6.2021 16:55 - 18:35 |
| Chair: Jaeyong Lee | Organizer: Igor Pruenster |
| E0437: R. Mena | |
| Beta-binomial stick-breaking non-parametric prior | |
| E0531: G. Koers | |
| On the non-i.i.d. misspecified Bernstein-Von Mises theorem | |
| E0487: G. Rebaudo, A. Fasano, A. Lijoi, I. Pruenster | |
| Compositions of discrete random probabilities for inference on multiple samples | |
| E0515: B. Franzolini, F. Ascolani, A. Lijoi, I. Pruenster | |
| Nonparametric priors with full-range borrowing of information |
| Session EO245 | Room: R07 |
| Topics in spatial statistics | Thursday 24.6.2021 16:55 - 18:35 |
| Chair: Anastassia Baxevani | Organizer: Anastassia Baxevani |
| E0686: D. Bolin | |
| Necessary and sufficient conditions for asymptotically optimal kriging of random fields on compact metric spaces | |
| E0714: A. Baxevani, C. Andreou | |
| Compound Poisson gamma process as a model for precipitation | |
| E0739: D. Hristopulos | |
| Random fields with truncated polynomial spectral density | |
| E0742: F. Lindgren | |
| Non-linear and joint models with the inlabru package |
| Session EC335 | Room: R05 |
| Contributions in methods and computations | Thursday 24.6.2021 16:55 - 18:35 |
| Chair: Stefan Van Aelst | Organizer: EcoSta |
| E0704: M. Hashiguchi, M. Okabe, H. Yadohisa | |
| Canonical correlation analysis for multimodal labeled data | |
| E0660: J.K. Kurle, X. Jiao | |
| Outlier testing in robust 2SLS models: An asymptotic study of the false outlier detection rate | |
| E0647: J. Kukacka | |
| Optimal moment-subset selection for the simulated method of moments using machine learning | |
| E0754: A. Bucci, Z. Liu, L. He | |
| Combining dimensionality reduction with neural networks for realized volatility forecasting |
| Parallel session G: EcoSta2021 | Friday 25.6.2021 | 08:00 - 09:40 |
| Session EO209 | Room: R01 |
| Statistical methods for handling high-dimensional/longitudinal data | Friday 25.6.2021 08:00 - 09:40 |
| Chair: MinJae Lee | Organizer: MinJae Lee |
| Session EO085 | Room: R02 |
| Novel statistical modeling of multivariate data | Friday 25.6.2021 08:00 - 09:40 |
| Chair: Anuradha Roy | Organizer: Anuradha Roy |
| E0298: T.-I. Lin | |
| Mixtures of factor analyzers with covariates for clustering multiply censored dependent variables | |
| E0473: A. Roy, T. Opheim | |
| Linear models for doubly multivariate data with block exchangeable covariance structure | |
| E0582: N. Diawara | |
| Copula-based bivariate Poisson time series models | |
| E0667: K. Hirose, K. Miura | |
| Hierarchical multiclass discriminant analysis via cross-validation |
| Session EO097 | Room: R03 |
| Advances in statistical methodologies and applications in medical sciences | Friday 25.6.2021 08:00 - 09:40 |
| Chair: Hua Shen | Organizer: Jingjing Wu |
| Session EO215 | Room: R04 |
| Bayesian methods with applications to sports, medicine, and time series | Friday 25.6.2021 08:00 - 09:40 |
| Chair: Zhihua Ma | Organizer: Yishu Xue, Jieying Jiao |
| E0505: H.-C. Yang, Y. Xue, G. Hu | |
| Zero-inflated Poisson model with clustered regression coefficients: an application to field goal attempts | |
| E0528: Z. Ma, C. Liu, J. Shen | |
| Nonparametric Bayesian changepoint model with signed beta process | |
| E0552: Q. Liu, G. Hu | |
| Non-negative matrix factorization on count data with concave pairwise group fusion | |
| E0535: Y. Gwon | |
| Bayesian network meta-regression for ordinal outcomes with uncertain categories |
| Session EO317 | Room: R05 |
| Statistical methods for network data | Friday 25.6.2021 08:00 - 09:40 |
| Chair: Yuan Zhang | Organizer: Yuan Zhang |
| Session EO297 | Room: R06 |
| Topological data analysis for socio-economics | Friday 25.6.2021 08:00 - 09:40 |
| Chair: Dorcas Ofori-Boateng | Organizer: Dorcas Ofori-Boateng |
| E0598: I. Segovia-Dominguez | |
| Forecasting COVID-19 spread with topological signatures of atmospheric conditions | |
| E0614: S. Rudkin, P. Dlotko, W. Qiu | |
| Applications of topological data analysis ball mapper in economics | |
| E0625: A.K. Dey, M. Yuvaraj, V. Lyubchich, Y. Gel, V. Poor | |
| Topological clustering of multilayer networks | |
| E0689: D. Ofori-Boateng, Y. Gel, I. Segovia-Dominguez, M. Kantarcioglu, C. Akcora | |
| Topology-based anomaly detection in dynamic multilayer networks |
| Session EO225 | Room: R07 |
| Novel methods and applications in statistics | Friday 25.6.2021 08:00 - 09:40 |
| Chair: Yeonhee Park | Organizer: Yeonhee Park, Mihye Ahn |
| E0577: S. Shin | |
| Sparse and efficient estimation with semiparametric models in meta-analysis | |
| E0541: S.J. Shin, J. Kang | |
| A forward approach for sufficient dimension reduction in binary classification | |
| E0603: J. Long, M.J. Ha | |
| Causal inference with hidden confounders: a comparison between two stage least squares and the causal Dantzig | |
| E0568: Y. Chen, Y. Chen | |
| Bayesian inference of the number of classes in restricted latent class models |
| Session EO227 | Room: R08 |
| Recent developments in climate/environmental statistics | Friday 25.6.2021 08:00 - 09:40 |
| Chair: Whitney Huang | Organizer: Whitney Huang |
| E0286: W. Chang, S. Bhatnagar, S. Kim, J. Wang | |
| A new computer model calibration framework based on deep neural network | |
| E0554: M. Jester, Y.-M. Chung, X. Gao, S. Day, K. Keegan | |
| Topological estimation of 2D image data via subsampling and applications | |
| E0567: S. Holan, R. Janicki, A. Raim, J. Maples | |
| Bayesian nonparametric multivariate spatial mixture mixed effects models | |
| E0725: A. Diaz | |
| Modeling the impacts of climate factors across the distribution of wildfires |
| Parallel session H: EcoSta2021 | Friday 25.6.2021 | 09:50 - 11:05 |
| Session EI009 | Room: R08 |
| Machine learning and approximation theory | Friday 25.6.2021 09:50 - 11:05 |
| Chair: Andreas Christmann | Organizer: Andreas Christmann |
| Session EO374 | Room: R01 |
| Advances in high-dimensional and complex data analysis | Friday 25.6.2021 09:50 - 11:05 |
| Chair: Debashis Paul | Organizer: Debashis Paul |
| E0324: A. Ishii, K. Yata, M. Aoshima | |
| High-dimensional classifiers under the strongly spiked eigenvalue model | |
| E0584: J. Namdari, A. Aue, D. Paul | |
| Spectral estimation for high-dimensional linear processes | |
| E0696: D. Paul, L. Wang | |
| Estimation of spectra of high-dimensional separable covariance matrices |
| Session EO071 | Room: R02 |
| Advances in causal inference | Friday 25.6.2021 09:50 - 11:05 |
| Chair: Luke Keele | Organizer: Luke Keele |
| Session EO121 | Room: R03 |
| Recent development in biostatistics | Friday 25.6.2021 09:50 - 11:05 |
| Chair: Kyuhyun Kim | Organizer: Sangwook Kang |
| E0292: J. Choi | |
| A two-phase approach to account for unmeasured confounding and censoring of a survival endpoint | |
| E0268: G. Goh, J. Yu | |
| Bayesian causal inference with some invalid instrumental variables | |
| E0593: K. Kim, S. Kang | |
| Smoothed quantile regression for censored residual lifetime |
| Session EO211 | Room: R04 |
| Advances in finite mixture models: Methodology and applications I | Friday 25.6.2021 09:50 - 11:05 |
| Chair: Abbas Khalili | Organizer: Abbas Khalili |
| Session EO125 | Room: R05 |
| Inference in statistical networks and graphical models | Friday 25.6.2021 09:50 - 11:05 |
| Chair: Kuang-Yao Lee | Organizer: Kuang-Yao Lee |
| E0235: J. Sun, K. Liao, T. Cai | |
| Learning healthcare delivery network with longitudinal electronic health records data | |
| E0587: K. Kim | |
| On sufficient graphical models | |
| E0672: K. Lee, Q. Chen, W. DeSarbo, L. Xue | |
| Estimating finite mixtures of ordinal graphical models |
| Session EO177 | Room: R06 |
| Multiple facets of dimension reduction | Friday 25.6.2021 09:50 - 11:05 |
| Chair: Lo-Bin Chang | Organizer: Lo-Bin Chang, Yoonkyung Lee |
| E0343: Y. Chung, T. Choi, D. Yang | |
| Nonparametric Bayesian latent factor model for multivariate functional clustering | |
| E0347: S. Lee, R. Dey, K. Nho | |
| Two-stage approach to address the over-fitting problem in partial least squares regression | |
| E0447: L.-B. Chang, E. Borenstein, W. Zhang, S. Geman | |
| Dimensionality reduction through conditional modeling |
| Session EO265 | Room: R07 |
| Recent advances in analysis of dependent data | Friday 25.6.2021 09:50 - 11:05 |
| Chair: Yi Shen | Organizer: Shuyang Bai |
| E0452: Y. Shen, J. Kang, P. Marriott, W. Qi | |
| Random topology in soft-thresholded Gaussian models | |
| E0748: R. Kulik | |
| Disjoint and sliding blocks estimators for heavy tailed time series | |
| E0652: R. Xie, S. Bai, P. Ma | |
| Optimal sampling designs for online estimation of streaming multi-dimensional time series |
| Parallel session I: EcoSta2021 | Friday 25.6.2021 | 11:15 - 12:30 |
| Session EO285 | Room: R01 |
| High-dimensional methods in observational studies | Friday 25.6.2021 11:15 - 12:30 |
| Chair: Daoji Li | Organizer: Tongtong Wu |
| E0185: A. Ertefaie, R. Strawderman | |
| Selective inference with robust Q-learning | |
| E0738: S. Yadlowsky | |
| Causal inference in high dimensions without sparsity |
| Session EO041 | Room: R03 |
| New flexible and robust statistical tools for biomedical research | Friday 25.6.2021 11:15 - 12:30 |
| Chair: Yanlin Tang | Organizer: Limin Peng |
| Session EO213 | Room: R04 |
| Advances in finite mixture models: Methodology and applications II | Friday 25.6.2021 11:15 - 12:30 |
| Chair: Abbas Khalili | Organizer: Abbas Khalili |
| E0634: T. Manole, N. Ho | |
| Uniform convergence rates for maximum likelihood estimation under two-component gaussian mixture models | |
| E0719: A. Khalili, D. Stephens | |
| Sparseness, consistency and model selection for Markov regime-switching autoregressives | |
| E0666: Y. Im, Y. Huang, J. Huang, S. Ma | |
| Bayesian hierarchical finite mixture of regression for histopathological imaging-based cancer data analysis |
| Session EO057 | Room: R05 |
| Complex data analysis using mixture models and empirical likelihood | Friday 25.6.2021 11:15 - 12:30 |
| Chair: Suyeon Kang | Organizer: Weixin Yao |
| E0590: Y. Fu | |
| Testing homogeneity in contaminated mixture models | |
| E0594: M. Huang | |
| Statistical inference for normal mixtures with unknown number of components | |
| E0727: S. Kang, K. Chen, W. Yao | |
| Dimensionality reduction in mixtures of multivariate linear regression |
| Session EO237 | Room: R06 |
| New challenges in complex data analysis | Friday 25.6.2021 11:15 - 12:30 |
| Chair: Yichuan Zhao | Organizer: Yichuan Zhao |
| E0518: J. Wang, F. Zhou, X. Feng | |
| Non-crossing quantile regression for deep reinforcement learning | |
| E0543: T. Wang | |
| A variable selection method for the joint model of longitudinal and survival data with its application | |
| E0544: Y. Zhao | |
| Bayesian jackknife empirical likelihood |
| Session EO093 | Room: R07 |
| New Frontiers in functional data analysis | Friday 25.6.2021 11:15 - 12:30 |
| Chair: Alexander Petersen | Organizer: Jane-Ling Wang |
| E0242: K.-Y. Lee, L. Li | |
| Functional dimension reduction via average Fr'echet derivatives | |
| E0335: A. Petersen, H.L. Shang, P. Kokoszka, H. Miao | |
| Forecasting of density functions with applications to cross-sectional and intraday returns | |
| E0580: A. Kneip, C. Carroll, H.-G. Mueller | |
| Cross-component registration for multivariate functional data: Application to growth curves |
| Session EO137 | Room: R08 |
| Recent advances in computational and methodological statistics | Friday 25.6.2021 11:15 - 12:30 |
| Chair: Wanjie Wang | Organizer: Naisyin Wang, Jin-Ting Zhang |
| E0735: W. Wang, Y. Yu, Y. Hu | |
| Graph matching beyond perfectly overlapping graphs | |
| E0420: Y. Kwon, W. Kim, J.-H. Won, M.C. Paik | |
| Wasserstein distributionally robust optimization with local perturbations | |
| E0423: S.-Y. Oh, A. Petersen, P. Cisneros-Velarde | |
| Distributionally robust formulation of the graphical lasso |
| Parallel session J: EcoSta2021 | Friday 25.6.2021 | 13:30 - 14:45 |
| Session EO301 | Room: R01 |
| Social issues in machine learning | Friday 25.6.2021 13:30 - 14:45 |
| Chair: Yongdai Kim | Organizer: Yongdai Kim |
| E0751: Y. Kim | |
| Within group fairness: A new concept for better between group fairness | |
| E0752: D. Kim, Y. Kim, Y. Choi | |
| Meta ANOVA: A model-agnostic tool for interpretable machine learning | |
| E0753: Y. Lee | |
| Challenges in making privacy protected data for public use |
| Session EO065 | Room: R02 |
| Some recent development on treatment effect study | Friday 25.6.2021 13:30 - 14:45 |
| Chair: Wei Luo | Organizer: Lixing Zhu |
| E0713: C. Ye, K. Guo, L. Zhu | |
| Doubly robust estimation for conditional treatment effect | |
| E0745: W. Luo | |
| On efficient dimension reduction with respect to the interaction between two response variables | |
| E0635: N. Zhou | |
| A Neyman-type orthogonality-based significance test for structure functions |
| Session EO129 | Room: R04 |
| Fintech and big data analytics | Friday 25.6.2021 13:30 - 14:45 |
| Chair: Mike So | Organizer: Mike So |
| Session EO159 | Room: R05 |
| Instabilities and irregularities in various data structures | Friday 25.6.2021 13:30 - 14:45 |
| Chair: Matus Maciak | Organizer: Michal Pesta, Matus Maciak |
| E0232: M. Pesta | |
| Changepoint and measurement errors | |
| E0295: J.E. Choi, D.W. Shin | |
| Testing constancy of correlation matrix based on self-normalization method | |
| E0297: M. Maciak, M. Pesta, S. Vitali | |
| Implied volatility surface estimation via quantile regularization |
| Session EO025 | Room: R06 |
| Statistical methods for functional data | Friday 25.6.2021 13:30 - 14:45 |
| Chair: Masaaki Imaizumi | Organizer: Ci-Ren Jiang |
| E0428: M. Imaizumi, T. Wakayama | |
| Fast convergence on perfect classification for functional data | |
| E0706: H.L. Shang, F. Ferraty | |
| Nonparametric density-on-density regression | |
| E0663: G. Van Bever, P. Ilmonen, L. Viitasaari, N. Shafik, T. Sottinen | |
| On optimal prediction of missing functional data with memory |
| Session EO193 | Room: R07 |
| Recent advances in causal inference | Friday 25.6.2021 13:30 - 14:45 |
| Chair: Linbo Wang | Organizer: Linbo Wang |
| E0731: D. Kong | |
| The promises of parallel outcomes | |
| E0701: Z. Lin, D. Kong, L. Wang | |
| Causal inference on non-linear spaces: Distribution functions and beyond | |
| E0687: M. Zhelonkin | |
| Robust estimation of treatment effects in a latent variable framework |
| Parallel session K: EcoSta2021 | Friday 25.6.2021 | 14:55 - 16:35 |
| Session EO027 | Room: R01 |
| Recent issues in econometrics | Friday 25.6.2021 14:55 - 16:35 |
| Chair: Jaeyoung Kim | Organizer: Jaeyoung Kim |
| E0673: H. Han | |
| Jackknife GMM with many weak moment conditions | |
| E0700: J.H. Lee, T. Andersen, V. Todorov | |
| Exploring systematic risk through high-frequency panel regressions | |
| E0705: S.Y. Chang | |
| Estimation of a level shift in panel data with fractionally integrated errors | |
| E0709: S. Han | |
| Optimal dynamic treatment regimes and partial welfare ordering |
| Session EO295 | Room: R02 |
| Perspectives of statistics for stochastic processes | Friday 25.6.2021 14:55 - 16:35 |
| Chair: Yuta Koike | Organizer: Yuta Koike |
| E0561: S. Eguchi, H. Masuda | |
| Stepwise model comparison for ergodic SDEs | |
| E0281: M. Goda | |
| Marked Hawkes process and sparse estimation | |
| E0401: K. Fujimori, Y. Shimizu, S. Sakamoto | |
| Moment convergence of the generalized maximum composite likelihood estimators for determinantal point processes | |
| E0564: Y. Koike, A. Oga | |
| Drift estimation for a multi-dimensional diffusion process using deep neural networks |
| Session EO081 | Room: R03 |
| New modeling and robust modeling for versatile data | Friday 25.6.2021 14:55 - 16:35 |
| Chair: Catherine Liu | Organizer: Catherine Liu |
| E0681: Y. Zhang, X. Zhang, H. Zhang, C. Liu | |
| FaMGLM: Factor analysis for a matrix-variated generalized linear model | |
| E0654: C. Zhong, C. Liu, J. Shen | |
| Semi-parametric Bayesian inference to linear transformation model with censored data | |
| E0734: L. Zhang | |
| Robust Bayesian analysis based on trimmed mean regression | |
| E0677: X. Fang, X. Zhang, S. Xu, X. Zhu, C. Liu | |
| Feature screening for generalized linear model with network structure |
| Session EO029 | Room: R04 |
| Recent advances in Bayesian Inference III | Friday 25.6.2021 14:55 - 16:35 |
| Chair: Antonio Lijoi | Organizer: Igor Pruenster |
| E0415: I. Antoniano-Villalobos, S. Padoan | |
| Towards data imputation of large observations via Bayesian inference for multivariate extremes | |
| E0566: P. Knaus, D. Winkler | |
| A Bayesian survival model for time-varying coefficients and unobserved heterogeneity | |
| E0470: M.A. Hadji, B. Szabo | |
| Distributed methods for Bayesian regression: Contraction rate \& uncertainty quantification | |
| E0550: D. Nieman, H. Zanten, B. Szabo | |
| Variational Bayes for regression with Gaussian process priors: A frequentist Bayesian analysis |
| Session EO271 | Room: R05 |
| Theory of machine learning and deep learning | Friday 25.6.2021 14:55 - 16:35 |
| Chair: Masaaki Imaizumi | Organizer: Masaaki Imaizumi |
| E0358: A. Okuno, K. Yano, H. Shimodaira | |
| Nonparametric link regression and its theoretical properties | |
| E0394: T. Maehara | |
| Theoretical analysis of graph classification problem | |
| E0456: R. Karakida | |
| Improving the trainability of deep neural networks: A perspective from the infinite width limit | |
| E0642: R. Nakada, M. Imaizumi | |
| Asymptotic risk of overparameterized likelihood models: Double descent theory for deep neural networks |
| Session EO273 | Room: R07 |
| Modeling spatial data with complex dependence structures | Friday 25.6.2021 14:55 - 16:35 |
| Chair: Pavel Krupskiy | Organizer: Pavel Krupskiy |
| Session EO207 | Room: R08 |
| Complex data analysis: Statistical learning and discovery | Friday 25.6.2021 14:55 - 16:35 |
| Chair: Subir Ghosh | Organizer: Subir Ghosh |
| E0628: A. Takemura | |
| Practical data science projects of faculty of data science of Shiga University | |
| E0579: N. Helwig | |
| Statistical learning via spectrally sparse smoothers | |
| E0618: S. Van Aelst, A.C. Christidis, R. Zamar | |
| Split modeling for high-dimensional logistic classifier ensembles | |
| E0585: H. Fujisawa, M. Takada | |
| Transfer learning on regression problem | |
| E0656: S. Ghosh | |
| Unsaturated log-linear model selection for categorical data analysis |
| Session EC338 | Room: R06 |
| Contributions in financial econometrics II | Friday 25.6.2021 14:55 - 16:35 |
| Chair: Wenying Yao | Organizer: EcoSta |
| E0183: D. Xia | |
| Explaining monetary spillovers: The matrix reloaded | |
| E0682: H. Ma | |
| Extracting time-varying betas of latent factors: Bridging econometrics and deep learning | |
| E0536: R. Moura, B. Candelon | |
| A multi-country model of the term structures of interest rates with a GVAR | |
| E0560: A. Renault, M. Garcin, N. Mangan, A. Al Wakil | |
| Sparse and stable index tracking with lasso and time-varying liquidity control |
| Parallel session L: EcoSta2021 | Friday 25.6.2021 | 16:45 - 18:25 |
| Session EO289 | Room: R01 |
| Modelling of time series and spatiotemporal data | Friday 25.6.2021 16:45 - 18:25 |
| Chair: Hiroshi Shiraishi | Organizer: Zudi Lu |
| E0165: Q. Liu, Y. Feng, R. Okui | |
| On the sparsity of Mallows model averaging estimator | |
| E0693: L. Wang, Z. Lu | |
| On threshold panel time series regression of cross-sectional dependence with application to climate financial analysis | |
| E0419: H. Shiraishi, Y. Shimizu | |
| Semiparametric estimation of optimal dividend barrier for Levy processes |
| Session EO150 | Room: R02 |
| New proposals for clustering complex data structures | Friday 25.6.2021 16:45 - 18:25 |
| Chair: Cristina Mollica | Organizer: Cristina Mollica |
| E0479: Z. Bakk | |
| Multilevel latent class analysis: Stepwise estimation | |
| E0514: R. Di Mari, R. Rocci, S.A. Gattone | |
| LASSO-penalized clusterwise linear regression modeling with local least angle regressions | |
| E0545: Y. Wei, L. Nguyen | |
| Finite mixture models with repeated measures | |
| E0571: C. Gormley | |
| Advances in model-based clustering of high-dimensional data |
| Session EO083 | Room: R03 |
| Modeling and inference for comprehensive data | Friday 25.6.2021 16:45 - 18:25 |
| Chair: Catherine Liu | Organizer: Catherine Liu |
| E0636: K.Y. Wong | |
| Score tests with incomplete covariates and high-dimensional auxiliary variables | |
| E0646: X. Zhang | |
| High-dimensional nonlinear matrix-variate normal factor model | |
| E0534: X. Zhang, H. Lian, D. Wang, G. Li | |
| A nonparametric subgroup analysis for quantile regression | |
| E0755: C. Liu | |
| Forecasting confirmed cases of the COVID-19 pandemic with a {migration-based} epidemiological model |
| Session EO039 | Room: R04 |
| Recent advances in Bayesian Inference IV | Friday 25.6.2021 16:45 - 18:25 |
| Chair: Sergios Agapiou | Organizer: Igor Pruenster |
| E0403: A. Lijoi, T. Rigon, I. Pruenster | |
| Finite-dimensional discrete random structures in Bayesian nonparametrics | |
| E0542: J. Greve, B. Gruen, S. Fruehwirth-Schnatter, G. Malsiner-Walli | |
| Leveraging Bayesian finite mixture modeling for better clustering solutions | |
| E0555: L. Vuursteen, B. Szabo, H. van Zanten | |
| Distributed testing in nonparametric models | |
| E0524: F. Gaffi, A. Lijoi, I. Pruenster | |
| Discrete nonparametric priors with fixed mean distributions |
| Session EO195 | Room: R05 |
| Theories of modern machine learning methodologies | Friday 25.6.2021 16:45 - 18:25 |
| Chair: Taiji Suzuki | Organizer: Taiji Suzuki |
| E0377: T. Suzuki, A. Nitanda, K. Tsuji | |
| Optimality and superiority of deep learning for estimating functions in variants of Besov spaces | |
| E0322: A. Nitanda, T. Suzuki | |
| Fast learning rates of averaged stochastic gradient descent for over-parameterized neural networks | |
| E0334: T. Matsubara, C. Oates, F.-X. Briol | |
| Approximation of Gaussian processes by bayesian neural networks | |
| E0333: M. Kanagawa, K. Muandet, S. Saengkyongam, S. Marukatat | |
| Counterfactual mean embeddings |
| Session EO059 | Room: R06 |
| Machine learning and robustness | Friday 25.6.2021 16:45 - 18:25 |
| Chair: Yiming Ying | Organizer: Yiming Ying, Andreas Christmann |
| E0512: B. Sriperumbudur | |
| Robust persistence diagrams using reproducing kernels | |
| E0491: Z.-C. Guo | |
| Analysis of online learning algorithms | |
| E0197: J. Lin | |
| Convergences of regularized algorithms with random projections | |
| E0179: A. Christmann | |
| On qualitative robustness of divide-and-conquer methods |
| Session EO299 | Room: R08 |
| Advances in time series modelling | Friday 25.6.2021 16:45 - 18:25 |
| Chair: Wai-keung Li | Organizer: Wai-keung Li |
| E0374: F. Guo | |
| Automated estimation of heavy-tailed vector error correction models | |
| E0484: W.-K. Li | |
| Some recent results on buffered (hysteretic) autoregressive model | |
| E0508: D. Luo, K. Zhu, H. Gong, D. Li | |
| Testing error distribution by kernelized Stein discrepancy in multivariate time series models | |
| E0586: M. Li | |
| Hybrid random weighting spectral test for multivariate white noise checking |
| Session EG296 | Room: R07 |
| Contributions in forecasting I | Friday 25.6.2021 16:45 - 18:25 |
| Chair: Manabu Asai | Organizer: EcoSta |
| E0318: M. Magris | |
| A vine-copula HAR forecasting model: Application to Dow Jones stocks | |
| E0645: J. Kim, N. Meddahi, M. Yamashita | |
| Forecast comparison tests under fat-tails | |
| E0481: G. Bakalli, S. Guerrier, O. Scaillet | |
| A penalized two-pass regression to predict stock returns with time-varying risk premia | |
| E0710: K. Khalid Mahmood | |
| A hybrid combined forecasting model of water discharge based on multiple linear regression and autoregressive models |
| Parallel session M: EcoSta2021 | Saturday 26.6.2021 | 08:00 - 10:05 |
| Session EO197 | Room: R01 |
| Recent advances in algorithms for statistical learning | Saturday 26.6.2021 08:00 - 10:05 |
| Chair: Eric Chi | Organizer: Eric Chi |
| E0181: J. Xu | |
| Biconvex clustering with adaptive feature selection | |
| E0245: X. Zhang, I. McKeague | |
| Significance testing for canonical correlation analysis in high dimensions | |
| E0273: J. Zeng, L. Li, X. Zhang | |
| Generalized liquid association analysis for multimodal neuroimaging | |
| E0533: J.-H. Won | |
| Proximity operator of the matrix perspective function and its applications | |
| E0551: M. Weylandt | |
| Dimension reduction and changepoint detection in network series |
| Session EO055 | Room: R02 |
| Recent applications of latent variable models | Saturday 26.6.2021 08:00 - 10:05 |
| Chair: Gongjun Xu | Organizer: Gongjun Xu |
| E0251: Z. Zhu, T. Wang, R. Samworth | |
| High-dimensional principal component analysis with heterogeneous missingness | |
| E0339: C. Wang | |
| Hypothesis testing methods for multivariate multi-occasion intra-individual change | |
| E0464: Z. Wu, M. Li | |
| Integrating sample similarities into latent class analysis: A tree-structured shrinkage approach | |
| E0465: S. Wang, Y. Chen, H. Xiao | |
| A latent variable model to measure fluency using response time and response accuracy | |
| E0724: K.M. Tan | |
| Time-varying overlapping clustering method via latent factor model |
| Session EO075 | Room: R04 |
| EcoSta journal Part B: Statistics | Saturday 26.6.2021 08:00 - 10:05 |
| Chair: Cristian Gatu | Organizer: Erricos Kontoghiorghes |
| E0177: H. Wang | |
| A fast adaptive lasso for the Cox regression via safe screening rules | |
| E0433: H.Y. Choi, S. Marron, N. Hayes | |
| A method for identifying uncorrelated outlier signals from high dimensional data | |
| E0648: A. Chaurasia | |
| Combining rules for F- and Beta-statistics from multiply-imputed data | |
| E0411: D. Li, D. Dunson | |
| Classification via local manifold approximation |
| Session EO233 | Room: R05 |
| Statistical inference with incomplete information | Saturday 26.6.2021 08:00 - 10:05 |
| Chair: Yen-Chi Chen | Organizer: Yen-Chi Chen |
| E0180: A. Franks, A. DAmour, J. Zheng | |
| Copula models for sensitivity analysis in observational causal inference | |
| E0203: D. Malinsky, R. Bhattacharya, I. Shpitser | |
| Causal inference under interference and network uncertainty | |
| E0345: Y.-C. Chen | |
| Pattern graph: A graphical approach to nonmonotone missing data | |
| E0404: S.W. Mogensen | |
| Estimation in Hawkes processes as a missing data problem | |
| E0438: A. Luedtke | |
| Adversarial Monte Carlo meta-learning in partially identified problems |
| Session EO109 | Room: R07 |
| EAC-ISBA session: Frontiers of spatial and temporal data modeling | Saturday 26.6.2021 08:00 - 10:05 |
| Chair: Won Chang | Organizer: Won Chang |
| E0502: W. Huang | |
| A combined physical-statistical approach for estimating storm surge risk | |
| E0676: Y. Jeon, S. Choi, W. Chang, J. Park | |
| Bayesian convolutional networks-based generalized linear model | |
| E0726: Y. Guan | |
| Multivariate spectral downscaling for PM2.5 species | |
| E0740: S. Lee, J. Park | |
| A scalable partitioned approach to model massive nonstationary non-Gaussian spatial datasets | |
| E0637: J. Stroud | |
| Dynamic spatio-temporal modeling |
| Session EC337 | Room: R03 |
| Contributions to statistical modelling and applications I | Saturday 26.6.2021 08:00 - 10:05 |
| Chair: Ramses Mena | Organizer: EcoSta |
| E0468: T. Mahmood, A. Iqbal, S. Kinat | |
| On the comparison of GLM-based charts for industrial processes | |
| E0364: S. Hyun, J. Bien, F. Ribalet, M. Cape | |
| Sparse Gaussian mixture regression with application to flow cytometry data analysis | |
| E0457: C.T. Ng, V.C. Nguyen | |
| Variable selection under multi-collinearity using modified log penalty | |
| E0702: V.H. Dao, D. Gunawan, M.-N. Tran, R. Kohn, G. Hawkins, S. Brown | |
| Efficient selection between hierarchical cognitive models: Cross-validation with variational Bayes | |
| E0756: L. Petrasek | |
| US stock market reaction to surprises in macroeconomic data announcements |
| Parallel session N: EcoSta2021 | Saturday 26.6.2021 | 10:15 - 11:55 |
| Session EO321 | Room: R01 |
| Recent advances in causal mediation analysis | Saturday 26.6.2021 10:15 - 11:55 |
| Chair: Yi Zhao | Organizer: Yi Zhao |
| E0595: C. Kim, M. Daniels, J. Hogan, C. Choirat, C. Zigler | |
| Bayesian methods for multiple mediators: Relating principal stratification and causal mediation | |
| E0631: A. Chakrabortty | |
| Inference for individual mediation effects and interventional effects in sparse high-dimensional causal graphical models | |
| E0728: S. Chu | |
| Mediation in the analysis of metabolomic data | |
| E0207: J. Hogan | |
| Discussion |
| Session EO231 | Room: R02 |
| Advances in analysis methodologies medical and biomedical applications | Saturday 26.6.2021 10:15 - 11:55 |
| Chair: Daniel Jeske | Organizer: Daniel Jeske |
| E0498: Y. Liu, X. Chen, S. Ma, Z. Zhang | |
| Efficient estimation of general treatment effects using neural networks with a diverging number of confounders | |
| E0510: W. Ma | |
| Learning fine-resolution chromosome conformation interaction maps | |
| E0581: D. Madigan | |
| Real real-world evidence | |
| E0589: S. VanSchalkwyk, D. Jeske | |
| A Bayesian longitudinal trend analysis of count data with Gaussian processes |
| Session EO243 | Room: R04 |
| Recent advances in the modeling of functional and high-dimensional data | Saturday 26.6.2021 10:15 - 11:55 |
| Chair: Xiaowei Wu | Organizer: Hongxiao Zhu |
| Session EO045 | Room: R05 |
| Recent advances in time series analysis | Saturday 26.6.2021 10:15 - 11:55 |
| Chair: Runmin Wang | Organizer: Xiaofeng Shao |
| E0162: Y. Rho, Y. Liu, H.J. Ahn | |
| Revealing cluster structures based on mixed sampling frequencies: Application to the state-level labor markets | |
| E0231: K. Zhu | |
| Testing for the martingale difference hypothesis in multivariate time series models | |
| E0259: C.E. Lee, X. Shao | |
| Volatility martingale difference divergence matrix for dimension reduction of multivariate volatility | |
| E0267: R. Wang, X. Shao | |
| Hypothesis testing for high-dimensional time series via self-normalization |
| Session EO275 | Room: R06 |
| Nonlinearity in applied econometrics | Saturday 26.6.2021 10:15 - 11:55 |
| Chair: Feng Yao | Organizer: Feng Yao |
| E0161: K. Sun, X. Geng | |
| Estimation of a partially linear seemingly unrelated regressions model: Application to a translog cost system | |
| E0208: Z. Wu, S. Yuan | |
| Financial openness and investment allocations in Chinese real sectors | |
| E0388: T. Wang, F. Yao, S. Kumbhakar | |
| A fixed effect additive stochastic frontier model with interactions and distribution free inefficiency | |
| E0506: F. Yao | |
| Efficient nonparametric estimation of regression discontinuity |
| Session EO261 | Room: R07 |
| Recent advances in functional data analysis | Saturday 26.6.2021 10:15 - 11:55 |
| Chair: Yuhang Xu | Organizer: Raymond Ka Wai Wong, Yuhang Xu |
| E0620: G. Wang, L. Wang, Y. Wang | |
| Statistical modeling and inference for next-generation functional data | |
| E0621: Y. Xu, Y. Li, Y. Qiu | |
| Growth dynamics for plant high-throughput phenotyping studies using hierarchical functional data analysis | |
| E0629: R.K.W. Wong, J. Wang, X. Zhang | |
| Low-rank covariance function estimation via functional unfolding | |
| E0640: K. He, S. Shen, L. Zhou | |
| Temporal-dependent principal component analysis of two-dimensional functional data |
| Session EO061 | Room: R08 |
| Mathematics of data science | Saturday 26.6.2021 10:15 - 11:55 |
| Chair: Ding-Xuan Zhou | Organizer: Ding-Xuan Zhou |
| E0204: H. Feng | |
| Chebyshev-type cubature formulas on weighted spheres | |
| E0389: M. Ha Quang | |
| Riemannian distances between infinite-dimensional covariance operators and Gaussian processes | |
| E0516: X. Guo, Q. Fu, T.-Y. Zhou, Y. Wang, K. Land | |
| Generalized linear regression with grouped and right-censored count data | |
| E0559: J. Fan | |
| Learning theory of weighted distance weighted discrimination |
| Session EG298 | Room: R03 |
| Contributions in forecasting II | Saturday 26.6.2021 10:15 - 11:55 |
| Chair: Donggyu Kim | Organizer: EcoSta |
| E0572: D. Li, A. Clements, C. Drovandi | |
| A Bayesian approach for more reliable tail risk forecasts | |
| E0657: R. Fan, J.H. Lee, Y. Shin | |
| Predictive quantile regression with mixed roots and increasing dimensions | |
| E0703: Y. Xu, T.-H. Lee | |
| Forecast encompassing in modal regression for equity premium prediction | |
| E0729: T. Ferreira, D. Cascaldi-Garcia, D. Giannone, M. Modugno | |
| Back to the present: Learning about the euro area through a now-casting model |
| Parallel session P: EcoSta2021 | Saturday 26.6.2021 | 13:55 - 15:35 |
| Session EO329 | Room: R01 |
| Recent advances in model selection and related topics | Saturday 26.6.2021 13:55 - 15:35 |
| Chair: Shinpei Imori | Organizer: Shinpei Imori |
| E0264: S. Hashimoto | |
| Robust bayesian regression with synthetic posterior | |
| E0299: K. Morikawa, K. Beppu | |
| On the verifiable identification condition in NMAR missing data analysis | |
| E0527: R. Oda, H. Yanagihara | |
| A consistent variable selection method with GIC in multivariate linear regression even when dimensions are large | |
| E0627: S. Imori | |
| Variable selection in high-dimensional multivariate linear regression models with group structure |
| Session EO051 | Room: R02 |
| Recent advances in statistics | Saturday 26.6.2021 13:55 - 15:35 |
| Chair: Yunjin Choi | Organizer: Yunjin Choi |
| E0306: G. Park | |
| Identifiability of structrual equation models | |
| E0348: C. Li | |
| Bayesian fixed-domain asymptotics for covariance parameters in gaussian random field models | |
| E0530: A.K.H. Kim, A. Guntuboyina | |
| Global rates of convergence in mixture density estimation | |
| E0549: B. Sun | |
| Semiparametric causal mediation analysis under unmeasured mediator-outcome confounding |
| Session EO089 | Room: R03 |
| Innovative theory and applications of hidden Markov models | Saturday 26.6.2021 13:55 - 15:35 |
| Chair: Xinyuan Song | Organizer: Xinyuan Song |
| Session EO047 | Room: R04 |
| Recent advances in Bayesian Inference V | Saturday 26.6.2021 13:55 - 15:35 |
| Chair: Marta Catalano | Organizer: Igor Pruenster |
| E0499: M. Chae | |
| Adaptive Bayesian inference for current status data on a grid | |
| E0570: S. Franssen, B. Szabo | |
| Frequentist coverage of empirical Bayesian uncertainty quantification using deep neural network regression | |
| E0489: N. Awaya, L. Ma | |
| Tree boosting for learning probability measures | |
| E0495: F. Ascolani, A. Lijoi, I. Pruenster | |
| Trees of random probability measures and Bayesian nonparametric modelling |
| Session EO035 | Room: R05 |
| Recent development of VAR and SVAR model | Saturday 26.6.2021 13:55 - 15:35 |
| Chair: Koichi Maekawa | Organizer: Koichi Maekawa |
| E0328: H. Morita | |
| Forecasting public investment using daily stock returns | |
| E0353: T. Kurita, J.L. Castle | |
| A dynamic econometric analysis of the dollar-pound exchange rate in an era of structural breaks and policy regime shifts | |
| E0680: T. Nakanishi, K. Maekawa, T. Senda | |
| Application of non-Gaussian SVAR model to the analysis of Japans quantitative easing monetary policy | |
| E0371: K. Maekawa, T. Nakanishi | |
| Estimation of non-Gaussian structural VAR model under a flexible quasi-log-likelihood function |
| Session EO073 | Room: R07 |
| EcoSta journal Part A: Econometrics | Saturday 26.6.2021 13:55 - 15:35 |
| Chair: Erricos Kontoghiorghes | Organizer: Erricos Kontoghiorghes |
| E0409: S. Hediger, G. De Nard, M. Leippold | |
| Size does matter: Big data machine learning portfolios | |
| E0182: S. Park, S. Kou | |
| A generalization of Friedman's permanent income hypothesis with a large, negative income shock | |
| E0386: V. Tendenan, R. Gerlach, C. Wang | |
| Bayesian estimation of realized EGARCH model to forecast tail risks | |
| E0402: D. Kim | |
| Adaptive robust large volatility matrix estimation based on high-frequency financial data |
| Session EC331 | Room: R06 |
| Contributions to statistical modelling and applications II | Saturday 26.6.2021 13:55 - 15:35 |
| Chair: Liming Xiang | Organizer: EcoSta |
| E0472: S. Pal, C. Heumann | |
| Unsupervised learning through generalized mixture model | |
| E0477: M.A. Ruiz Reina | |
| Statistical learning: Bernoulli time series modelling for discrete decision choice | |
| E0523: E. Zarova | |
| Development of data mining trajectories based on the statistical matching resources | |
| E0463: M. Marbac, M. du Roy de Chaumaray | |
| Clustering data with nonignorable missingness usingsemi-parametric mixture models |
| Parallel session Q: EcoSta2021 | Saturday 26.6.2021 | 15:45 - 17:25 |
| Session EO105 | Room: R01 |
| Theories and methodologies for high-dimensional data analysis | Saturday 26.6.2021 15:45 - 17:25 |
| Chair: Aki Ishii | Organizer: Kazuyoshi Yata |
| E0217: S.-H. Wang, S.-Y. Huang, T.-L. Chen | |
| On asymptotic normality of CDM-PCA in HDLSS | |
| E0355: Y. Nakayama, K. Yata, M. Aoshima | |
| Clustering by kernel PCA with Gaussian kernel and tuning for high-dimensional data | |
| E0316: K. Yata, A. Ishii, M. Aoshima | |
| Tests for covariance structures in high-dimensional data | |
| E0688: A. Steland | |
| Change-testing for high-dimensional econometric factor models |
| Session EO346 | Room: R04 |
| Recent advances in Bayesian inference VI | Saturday 26.6.2021 15:45 - 17:25 |
| Chair: Minwoo Chae | Organizer: Igor Pruenster |
| E0427: R. Argiento, S. Montagna, A. Lanteri | |
| A Bayesian nonparametric approach for functional regression with application to sport data | |
| E0482: G. Zens, H. Wagner, S. Fruehwirth-Schnatter | |
| Ultimate Polya gamma samplers: Efficient MCMC for possibly imbalanced binary and categorical data | |
| E0546: W. Kim, P. Jenkins, C. Yau | |
| Learning multimorbidity and its temporal dynamics with the Wright-Fisher Indian buffet process | |
| E0547: D. Hosszejni, G. Kastner | |
| Modeling univariate and multivariate stochastic volatility in R with stochvol and factorstochvol |
| Session EO315 | Room: R05 |
| Advanced computational statistics for machine learning | Saturday 26.6.2021 15:45 - 17:25 |
| Chair: Jong-june Jeon | Organizer: Jong-june Jeon |
| E0265: D. Yu, Y.-G. Choi, S. Lee | |
| An efficient parallel block coordinate descent algorithm for large-scale precision matrix estimation using GPUs | |
| E0288: D. Kim | |
| Accelerated gradient method for convex-concave saddle-point problems | |
| E0405: K. Yano, F. Komaki, Y. Takasu | |
| On proper local scoring rules for spherical data | |
| E0665: J.-J. Jeon, S.J. Moon | |
| Regularized Babington Smith ranking models |
| Session EO111 | Room: R07 |
| Recent advances in complex time series analysis | Saturday 26.6.2021 15:45 - 17:25 |
| Chair: Haeran Cho | Organizer: Haeran Cho |
| E0434: H. Maeng, P. Fearnhead, I. Eckley | |
| Collective anomaly detection in high-dimensional VAR models | |
| E0455: A. Safikhani, A. Safikhani, Y. Bai, G. Michailidis | |
| Threshold block fused lasso method for break point detection in high-dimensional time series models | |
| E0496: E. McGonigle, H. Cho | |
| Changepoint detection for complex time series data | |
| E0698: C. Zheng | |
| Temporal aggregation on locally stationary time series |
| Session EC332 | Room: R06 |
| Contributions in econometric modelling | Saturday 26.6.2021 15:45 - 17:25 |
| Chair: Alexandra Soberon | Organizer: EcoSta |
| E0718: A. Soberon, J.M. Rodriguez-Poo, A. Musolesi | |
| A semiparametric panel data model with common factors and spatial dependence: The knowledge production function | |
| E0569: C. Kountzakis, K. Gkillas | |
| Negatively valued functions in economic modeling | |
| E0583: J. Sila, L. Kristoufek | |
| Cryptoassets markets as dynamic networks: Investigating connectedness, investment horizons, and systemic risk | |
| E0307: P. Brakatsoulas | |
| Credit rating downgrade risk on equity returns |
| Session EG240 | Room: R02 |
| Contributions in nonparametric statistics and applications | Saturday 26.6.2021 15:45 - 17:25 |
| Chair: Germain Van Bever | Organizer: EcoSta |
| E0462: K. Salehzadeh Nobari | |
| Pair copula constructions of point-optimal sign-based tests for predictive linear and non-linear regressions | |
| E0692: A. Jokiel-Rokita | |
| Quantile versions of inequality curves and inequality measures | |
| E0730: A. Srakar | |
| Wavelet regression for symplectic data from a Bayesian and nonparametric Bayes perspective | |
| E0562: M. Garcin, M. Nicolas | |
| From the non-parametric estimation of tail dependence coefficients to portfolio diversification |
| Session EG377 | Room: R03 |
| Contributions in survival analysis | Saturday 26.6.2021 15:45 - 17:25 |
| Chair: Binyan Jiang | Organizer: EcoSta |
| E0205: Y. Cho, C. Hu, D. Ghosh | |
| Analysis of regression discontinuity designs using censored data | |
| E0658: F.-Z. Jaouimaa, I.D. Ha, K. Burke | |
| Hierarchical multi-parameter regression survival models | |
| E0664: W.B. Ewnetu, I. Gijbels, A. Verhasselt | |
| Flexible two-piece distributions for right censored survival data | |
| E0685: L. McQuaid, K. Burke | |
| Penalized multi-parameter regression modelling |