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Divergence-based tests for model diagnostic

SYSNO ASEP	0312534
Document Type	J - Journal Article
R&D Document Type	Journal Article
Subsidiary J	Článek ve WOS
Title	Divergence-based tests for model diagnostic
Title	Divergenční testy pro diagnostiku modelu
Author(s)	Hobza, Tomáš (UTIA-B) Esteban, M. D. (ES) Morales, D. (ES) Marhuenda, Y. (ES)
Source Title	Statistics & Probability Letters. - : Elsevier - ISSN 0167-7152 Roč. 78, č. 13 (2008), s. 1702-1710
Number of pages	9 s.
Publication form	www - www
Language	eng - English
Country	NL - Netherlands
Keywords	goodness of fit ; devergence statistics ; GLM ; model checking ; bootstrap
Subject RIV	BB - Applied Statistics, Operational Research
R&D Projects	1M0572 GA MŠMT - Ministry of Education, Youth and Sports (MEYS)
CEZ	AV0Z10750506 - UTIA-B (2005-2011)
UT WOS	000259688500003
DOI	10.1016/j.spl.2008.01.007
Annotation	Pearson's x2 test, and more generally, divergence-based tests of goodness-of-fit are asymptotically x2-distributed with m-1 degrees of freedom if the numbers of cells m is fixed, the observations are iid and the cell probabilities and model parameters are completely specified. Jiang (2001) proposed a nonstandard x2 test to check distributional assumptions for the case of observations not identically distributed. Under the same set up, in this paper a family of divergence-based tests are introduced and their asymptotic distributions are derived. In additions bootstrap tests based on the given divergence test statistics are considered. Applications to generalized linear models diagnostic are proposed. A simulation study is carried out to investigate performance of several power divergence tests.
Workplace	Institute of Information Theory and Automation
Contact	Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201.
Year of Publishing	2009

Number of the records: 1