Journal- Programme Changes (11.Dec.2015)
- Winter Course Material (08.Dec.2015)
- Tutorial Material (07.Dec.2015)
- Book of Abstracts (16.Nov.2015)
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The 8th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2015) will take place at the Senate House, University of London, UK, 12-14 December 2015. Tutorials will be given on Friday 11th of December 2015 and the CRoNoS Winter Course on Robust methods and multivariate extremes will take place the 9-10 December 2015. The series of ERCIM conferences of the WG CMStatistics will be renamed from now as CMStatistics conferences. Thus, CMStatistics 2015 follows ERCIM 2014 in this series.
This conference is organized by the ERCIM Working Group on Computational and Methodological Statistics (CMStatistics), Queen Mary University of London, Birkbeck University of London and Imperial College London. The journal Computational Statistics & Data Analysis publishes selected papers in special peer-reviewed, or regular issues.
Click on the following link if you wish to become a member of CMStatistics. For further information please contact info@cmstatistics.org or visit the CMStatistics website.
The Conference will take place jointly with the 9th International Conference on Computational and Financial Econometrics (CFE 2015). The conference has a high reputation of quality presentations. The last editions of the joint conference CFE-ERCIM gathered over 1250 participants.
All topics within the Aims and Scope of the ERCIM Working Group CMStatistics will be considered for oral and poster presentation.
Topics includes, but not limited to: robust methods, statistical algorithms and software, high-dimensional data analysis, statistics for imprecise data, extreme value modeling, quantile regression and semiparametric methods, model validation, functional data analysis, Bayesian methods, 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 and computational statistics for clinical research.