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Displaying similar documents to “Testing in locally conic models, and application to mixture models”

The likelihood ratio test for general mixture models with or without structural parameter

Jean-Marc Azaïs, Élisabeth Gassiat, Cécile Mercadier (2009)

ESAIM: Probability and Statistics

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This paper deals with the likelihood ratio test (LRT) for testing hypotheses on the mixing measure in mixture models with or without structural parameter. The main result gives the asymptotic distribution of the LRT statistics under some conditions that are proved to be almost necessary. A detailed solution is given for two testing problems: the test of a single distribution against any mixture, with application to Gaussian, Poisson and binomial distributions; the test of the number...

Testing in locally conic models, and application to mixture models

Didier Dacunha-Castelle, Elisabeth Gassiat (2010)

ESAIM: Probability and Statistics

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In this paper, we address the problem of testing hypotheses using maximum likelihood statistics in non identifiable models. We derive the asymptotic distribution under very general assumptions. The key idea is a local reparameterization, depending on the underlying distribution, which is called locally conic. This method enlights how the general model induces the structure of the limiting distribution in terms of dimensionality of some derivative space. We present various applications...