CMStatistics

The working group (WG) CMStatistics focuses on all computational and methodological aspects of statistics. Of particular interest is research in important areas of statistical application in which computational and/or methodological aspects play a major role. The aim is threefold: first, to consolidate research in computational and methodological statistics that is scattered throughout Europe; second, to provide researchers with a network through which they can obtain unrivalled access to information on the latest developments in computational and methodological statistics and their applications; and third, to produce high-quality, high-impact publications at the broad interface of computing, methodological statistics and their applications.

The Elsevier journals Computational Statistics and Data Analysis (CSDA) and Econometrics and Statistics (EcoSta) are the official journals of the CMStatistics network. CMStatistics also publishes the Annals of Statistical Data Science as a supplement to Part B: Statistics of Econometrics and Statistics.

Those wishing to join CMStatistics can affiliate through the following link. For further information, please contact info@cmstatistics.org.

Organization and Activities
The WG covers a wide range of research areas in computational and methodological statistics. Affiliates may act within the framework of the WG to advance and develop their own research agendas. They submit joint research proposals, organize sessions, tracks, and tutorials during the annual WG meetings, and contribute to the editorial activities of Econometrics and Statistics (EcoSta), including its special issues.
Next Events

CFE-CMStatistics 2026
20th International Conference on Computational and Financial Econometrics (CFE) and Computational and Methodological Statistics (CMStatistics)
12–14 December 2026, HTW Berlin, Berlin, Germany.

EcoSta 2027
11th International Conference on Econometrics and Statistics (EcoSta 2027)
6–9 July 2027, ShanghaiTech University, Shanghai, China.

Scope
The scope of the WG is broad enough to include researchers in all areas of methodological statistics and computing that influence the development and application of statistical techniques. Applications of statistics across a wide range of disciplines are strongly represented. These areas include economics, medicine, epidemiology, biology, finance, physics, chemistry, climatology, and communications. The breadth of topics addressed, together with the depth of their coverage, establishes the WG as an essential research network at the interdisciplinary intersection of advanced computational and methodological statistics.