Combinatorial Inference in Geometric Data Analysis - Le Roux, Brigitte
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Présentation Combinatorial Inference In Geometric Data Analysis de Le Roux, Brigitte Format Broché
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Résumé : Combinatorial Inference in Geometric Data Analysis gives an overview of multidimensional statistical inference methods applicable to clouds of points that make no assumption on the process of generating data or distributions, and that are not based on random modelling but on permutation procedures recasting in a combinatorial fr
Biographie: Brigitte Le Roux is associate researcher at Laboratoire de Math?matiques Appliqu?es (MAP5/CNRS) of the Paris Descartes university and at the political research center of Sciences-Po Paris (CEVIPOF/CNRS). She completed her doctoral dissertation in applied mathematics at the Facult? des Sciences de Paris in 1970 that was supervised by Jean-Paul Benz?cri. She has contributed to numerous theoretical research works and full scale empirical studies involving Geometric Data Analysis. She has authored and co-authored nine books, especially on Geometric Data Analysis (2004, Kluwer Academic Publishers) and Multiple Correspondence Analysis (2010, QASS series of Sage publications, n? 163). Sol?ne Bienaise is data scientist at Coheris (company). She completed her doctoral dissertation in applied mathematics in 2013 at the Paris Dauphine University, under the direction of Pierre Cazes and Brigitte Le Roux. Jean-Luc Durand is associate professor at the Psychology department and researcher at LEEC (Laboratoire d'Ethologie Exp?rimentale et Compar?e) of Paris 13 University. He completed his doctoral dissertation in Psychology at Paris Descartes University in 1989, supervised by Henry Rouanet. He teaches statistical methodology in psychology and ethology.
Sommaire: Euclidean Cloud. Geometric Typicality Test. Set-Theoretic Typicality Test. Homogeneity Tests. Mathematical Bases. Research Case Studies.
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