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  • Programme (18.Nov.2021)
  • Important dates (13.Sep.2021)
  • Publications (07.Apr.2021)
  • Organized Sessions (07.Apr.2021)
  • Committees (07.Apr.2021)


  • Sponsored by
    CMStatistics 2021 hybrid conference

    The 14th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2021) will be hosted by King's College London, 18-20 December 2021. Tutorials will also be given on Friday the 17th of December 2021.

    Due to the COVID-19 pandemic, the conference will be hybrid. The keynote talks, the special invited sessions, the hybrid organized sessions, and the virtual sessions will be live-streamed for all the conference participants.

    This conference is organized by the CMStatistics, King's Business School, and King's Department of Mathematics. The journal Econometrics and Statistics (EcoSta) and the CSDA Annals of Statistical Data Sciences 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 15th International Conference on Computational and Financial Econometrics (CFE 2021). The conference has a high reputation for quality presentations. The last in-person edition of the joint conference CFE-CMStatistics gathered over 1900 participants, while about 1100 participants attended the virtual CFE-CMStatistics 2020.

    Aims and Scope

    All topics within the Aims and Scope of the ERCIM Working Group CMStatistics will be considered for oral and poster presentation.

    Topics include, but 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 that contain strong computational, statistical, or econometric elements or substantive data-analytic components will also be considered for publication either in the CSDA Annals of Statistical Data Sciences or in Econometrics and Statistics.