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

Jean-Marc Azaïs; Élisabeth Gassiat; Cécile Mercadier

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Displaying similar documents to “The likelihood ratio test for general mixture models with or without structural parameter”

Testing in locally conic models, and application to mixture models

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Testing in locally conic models, and application to mixture models

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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...