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Title	MTests of Independence for Sparse Contingency Tables and Beyond
Creator	Neslehova, Johanna
Publisher	Banff International Research Station for Mathematical Innovation and Discovery
Date Issued	2013-05-21
Description	New statistics are proposed for testing the hypothesis that arbitrary random variables are mutually independent. These tests are consistent and well-behaved for any type of data, even for sparse contingency tables and tables whose dimension depends on the sample size. The statistics are Cramer-von Mises and Kolmogorov-Smirnov type functionals of the empirical checkerboard copula. The asymptotic behavior of the corresponding empirical process will be characterized and illustrated; it will also be shown how replicates from the limiting process can be generated using a multiplier bootstrap procedure. As will be seen through simulations, the new tests are considerably more powerful than those based on the Pearson chi squared, likelihood ratio, and Zelterman statistics often used in this context.
Extent	30 minutes
Subject	Mathematics Statistics Probability theory and stochastic processes
Type	Moving Image
FileFormat	video/mp4
Language	eng
Notes	Author affiliation: McGill University
Series	BIRS Workshop Lecture Videos (Banff, Alta)
Date Available	2014-10-03
Provider	Vancouver : University of British Columbia Library
Rights	Attribution-NonCommercial-NoDerivs 2.5 Canada
DOI	10.14288/1.0044031
URI	http://hdl.handle.net/2429/50578
Affiliation	Non UBC
Peer Review Status	Unreviewed
Scholarly Level	Faculty
Rights URI	http://creativecommons.org/licenses/by-nc-nd/2.5/ca/
AggregatedSourceRepository	DSpace

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