Displaying similar documents to “The likelihood ratio test for the number of components in a mixture with Markov regime”

The likelihood ratio test for the number of components in a mixture with Markov regime

Elisabeth Gassiat, Christine Keribin (2010)

ESAIM: Probability and Statistics

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We study the LRT statistic for testing a single population i.i.d. model against a mixture of two populations with Markov regime. We prove that the LRT statistic converges to infinity in probability as the number of observations tends to infinity. This is a consequence of a convergence result of the LRT statistic for a subproblem where the parameters are restricted to a subset of the whole parameter set.

Large deviations and full Edgeworth expansions for finite Markov chains with applications to the analysis of genomic sequences

Pierre Pudlo (2010)

ESAIM: Probability and Statistics

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To establish lists of words with unexpected frequencies in long sequences, for instance in a molecular biology context, one needs to quantify the exceptionality of families of word frequencies in random sequences. To this aim, we study large deviation probabilities of multidimensional word counts for Markov and hidden Markov models. More specifically, we compute local Edgeworth expansions of arbitrary degrees for multivariate partial sums of lattice valued functionals of finite...

Inference about stationary distributions of Markov chains based on divergences with observed frequencies

María Luisa Menéndez, Domingo Morales, Leandro Pardo, Igor Vajda (1999)

Kybernetika

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For data generated by stationary Markov chains there are considered estimates of chain parameters minimizing φ –divergences between theoretical and empirical distributions of states. Consistency and asymptotic normality are established and the asymptotic covariance matrices are evaluated. Testing of hypotheses about the stationary distributions based on φ –divergences between the estimated and empirical distributions is considered as well. Asymptotic distributions of φ –divergence test...