Fuzzy Statistical Analysis
Description:
Fuzzy sets are increasingly used in Statistics to model non-random uncertainty that often arises in the management of stochastic experiments. Thus, although the random mechanisms are usually properly formalized by using probabilistic tools, fuzzy sets are considered to describe different sources of imprecision in connection with both empirical data (especially linguistic data, expert opinions/judgments/perceptions, as well as various kinds of ill-observed statistical data) and/or models for data analysis. The fuzzy statistical analysis is nowadays applied in different sciences, as Economics, Biomedicine, Bioinformatics, Ecology, Geology, etc. to manage complex problems involving heterogeneous information. Special (but not exclusive) topics are regression, cluster analysis and inference with fuzzy data. In spite of the impact of this growing literature, there is room for further developments in several directions, including foundations, methodology and applications of the use of fuzzy sets in Statistics.
Focus:
This track offers a forum for discussing and comparing different viewpoints and proposals in this area. Particular topics for contributions of this track are:- Statistical testing and inference techniques using fuzzy data.
- Fuzzy models in data analysis.
- Fusion methods, uncertainty propagation.
- Use of Possibility Theory in Statistics.
- Practical representations of imprecise probabilistic information.
- Comparison between fuzzy and traditional (crisp) statistical methods.
- Applications of fuzzy statistical methods to Biomedicine, Finance and Economics, Social sciences and Psychology, Environmental sciences, Technology, etc.
Many of these topics are strongly connected with the Cost Action IC0702 Combining Soft Computing Techniques and Statistical Methods to Improve Data Analysis Solutions. The 4th Working Groups Meeting of this Cost Action, gathering more than 40 European researchers in this area, will take place the 27-28 October 2009. Special sessions for contributions of the Cost Participants will be organized.
Full papers containing a strong computational or data analytic component will be considered for publication in the second Special Issue on Fuzzy Sets in Statistical Analysis of the journal Computational Statistics and Data Analysis. All submissions must contain original unpublished work not being considered for publication elsewhere. Submissions will be refereed according to standard procedures for CSDA.
Co-Chairs:
- Ana Colubi, University of Oviedo, Spain.
- Didier Dubois Universite Paul Sabatier, France.
- Maria Angeles Gil University of Oviedo, Spain.
- Frank Klawonn University of Applied Sciences, Wolfenbuettel, Germany.
Created by Computing & Statistics 2007