This workshop is associated with the new supplement of the journal Computational Statistics & Data Analysis, the Annals of Statistical Data Science (SDS). The workshop and the Annals of SDS are promoted by the CMStatistics network. The journals Computational Statistics & Data Analysis (CSDA) and Econometrics and Statistics (EcoSta) are the official publications of CMStatistics.
The Annals and the Workshop of Statistical Data Science will serve as an outlet for research using advanced computational and/or statistical methods for tackling challenging data analytic problems. They will become a valuable resource for well-founded theoretical and applied data-driven research. Significant computational or statistical methodological component for data analytics will be considered. In particular, contributions at the interface of computing, statistics addressing problems involving large and/or complex data are welcome. Emphasis is given to comprehensive and reproducible research, including data-driven methodology, algorithms and software.
Dates: 26 August - 28 August 2022 (Friday afternoon to Sunday afternoon)
Venue: Department of Statistical Sciences "Paolo Fortunati", University of Bologna, via delle Belle Arti, n.41, 40126 Bologna, Italy.
Organizers: CMStatistics, CSDA and EcoSta.
Local Organizing Committee and co-chairs: Ana Colubi, Erricos Kontoghiorghes, M. Brigida Ferraro, Marzia Freo, Alessandra Luati.
SPC: Elvezio Ronchetti, Ivan Kojadinovic, Bertrand Clarke, Xinyuan Song, Michele Guindani, Peter Winker, Chenlei Leng, Stefano Castruccio, Taps Maiti, Igor Pruenster, Hans-Georg Mueller, Juan Romo, Cheng Yong Tang, Jane-Ling Wang.
Peter Rousseeuw, KU Leuven, Belgium.
Patrick J. Wolfe, Purdue University, United States.
- SO004: Clustering of complex data structures
Organizers: Maria Brigida Ferraro - SO006: Funcitonal and object data analysis
Organizers: Jane-Ling Wang - SO008: Joint modeling of longitudinal and time-to-event data
Organizers: Xinyuan Song - SO010: Text based indicators in economics and finance
Organizers: Peter Winker - SO012: Recent advances in dimension reduction and related methods
Organizers: Hiroshi Yadohisa, Yuichi Mori - SO015: Bayesian learning
Organizers: Igor Pruenster - SO017: Methodological and computational aspects of sequential change point detection
Organizers: Ivan Kojadinovic - SO019: Machine learning for spatial analysis
Organizers: Bertrand Clarke - SO021: TBA
Organizers: Taps Maiti - SO023: Contemporary computational and methodological challenges in environmental data
Organizers: Stefano Castruccio - SO025: High-dimensional statistics
Organizers: Chenlei Leng - SO027: Bayesian nonparametric and its applications
Organizers: Michele Guindani - SO031: Flexible models for the analysis and classification of heterogeneous data
Organizers: Geoffrey McLachlan