Lectures and seminars in "Advances in Combined Permutation Tests" by
Prof. Stefano Bonnini

Faculty of Business, Management and Economics, Faculty of Computing, and Laboratory for Perceptual and Cognitive Systems at the Faculty of Computing invite to

Lectures and Seminars in "Advances in Combined Permutation Tests" by Prof. Stefano Bonnini
Department of Economics and Management
University of Ferrara, Italy

Prof. Bonnini is a leading expert working on advanced methods in non-parametric statistics. He is an author of "Nonparametric Hypothesis Testing. Rank and Permutation Methods with Applications in R" (2014; Wiley: Chichester) which will be the main focus of his lectures and seminars.

In several application problems, the phenomena under study are multidimensional. Therefore, these phenomena are represented by multivariate variables. In multivariate inferential problems, such as tests of hypotheses for comparing two or more populations, where data are assumed to be determinations of random variables, standard parametric methods (e.g. likelihood ratio test, Hotelling T2 test, ...), when applicable, require stringent assumptions that make them non robust and often inappropriate.
The proposed combined nonparametric test, is based on the breakdown of the problem into as many sub-problems as many variables, and on the application of a univariate permutation test for each sub-problem. The combination of the permutation significance level functions of each test provides a unique test statistic (and a unique p-value) to solve the multivariate problem. 

Bonnini S, Corain L, Marozzi M, Salmaso L (2014). Nonparametric Hypothesis Testing: Rank and Permutation Methods with Applications in R. Wiley: Chichester

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