EFFECTS OF STATISTICAL DEPENDENCE ON MULTIPLE TESTING UNDER A HIDDEN MARKOV MODEL
The performance of multiple hypothesis testing is known to be affected by the statistical dependence among random variables involved. The mechanisms responsible for this, however, are not well understood. We study the effects of the dependence structure of a finite state hidden Markov model (HMM) on...
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| Veröffentlicht in: | The Annals of statistics 2011-02, Vol.39 (1), p.439-473 |
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| creator | Chi, Zhiyi |
| description | The performance of multiple hypothesis testing is known to be affected by the statistical dependence among random variables involved. The mechanisms responsible for this, however, are not well understood. We study the effects of the dependence structure of a finite state hidden Markov model (HMM) on the likelihood ratios critical for optimal multiple testing on the hidden states. Various convergence results are obtained for the likelihood ratios as the observations of the HMM form an increasing long chain. Analytic expansions of the first and second order derivatives are obtained for the case of binary states, explicitly showing the effects of the parameters of the HMM on the likelihood ratios. |
| doi_str_mv | 10.1214/10-AOS822 |
| format | Article |
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| source | Jstor Complete Legacy; EZB-FREE-00999 freely available EZB journals; Project Euclid Complete; JSTOR Mathematics & Statistics |
| subjects | 62H15 62M02 contraction Determinism Ergodic theory Exact sciences and technology FDR General topics HMM Hypothesis testing Markov analysis Markov chains Markov models Mathematical procedures Mathematical theorems Mathematics multiple hypothesis testing Multivariate analysis nonlinear filtering Nonparametric inference Parametric inference Perceptron convergence procedure Probability and statistics Random variables Sciences and techniques of general use Statistics Studies Transition probabilities |
| title | EFFECTS OF STATISTICAL DEPENDENCE ON MULTIPLE TESTING UNDER A HIDDEN MARKOV MODEL |
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