The 16th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2023) will be hosted by HTW Berlin, University of Applied Sciences (Wilhelminenhof campus), Berlin, Germany, 16-18 December 2023. Tutorials will also be given from 13th to 15th of December 2023.
The conference will be hybrid:
This conference is organized by the CMStatistics and HTW Berlin, University of Applied Sciences. The journals Econometrics and Statistics (EcoSta) and Computational Statistics and Data Analysis (CSDA) are the main sponsors of the conference. For further information please contact info@CMStatistics.org or visit the CMStatistics website. Click on the following link if you wish to become a member of CMStatistics.
The Conference will take place jointly with the 17th International Conference on Computational and Financial Econometrics (CFE 2023). It has a high reputation for quality presentations. The last edition of the joint conference CFE-CMStatistics gathered over 1950 participants.
All topics within the Aims and Scope of the ERCIM Working Group CMStatistics will be considered for oral and poster presentation.
Topics include, but are not limited to, robust methods, statistical algorithms and software, high-dimensional data analysis, statistics for complex data, extreme value modeling, quantile regression and semiparametric methods, model validation, functional data analysis, Bayesian methods, biostatistics, optimization heuristics in estimation and modelling, computational econometrics, quantitative finance, statistical signal extraction and filtering, small area estimation, latent variable and structural equation models, mixture models, matrix computations in statistics, time series modeling and computation, optimal design algorithms, causal inference, network data, graphical models, and computational statistics for clinical research.
Those papers containing strong computational, statistical, or econometric elements or substantive data-analytic components can be submitted for publication either in the CSDA Annals of Statistical Data Sciences or Econometrics and Statistics.