Adaptive estimation of the transition density of a particular hidden Markov chain

dc.creatorLacour, Claire
dc.date2006-11-22
dc.date.accessioned2026-07-07T09:28:41Z
dc.date.available2026-07-07T09:28:41Z
dc.descriptionWe study the following model of hidden Markov chain: $Y_i=X_i+ε_i$, $ i=1,...,n+1$ with $(X_i)$ a real-valued positive recurrent and stationary Markov chain and $(ε_i)_{1\leq i\leq n+1}$ a noise independent of the sequence $(X_i)$ having a known distribution. We present an adaptive estimator of the transition density based on the quotient of a deconvolution estimator of the density of $X_i$ and an estimator of the density of $(X_i,X_{i+1})$. These estimators are obtained by contrast minimization and model selection. We evaluate the $L2$ risk and its rate of convergence for ordinary smooth and supersmooth noise with regard to ordinary smooth and supersmooth chains. Some examples are also detailed.
dc.identifierhttps://arxiv.org/abs/math/0611681
dc.identifierhttp://arxiv.org/abs/math/0611681
dc.identifierJournal of Multivariate Analysis 99, 5 (2008) 787-814
dc.identifierdoi:10.1016/j.jmva.2007.04.006
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/157514
dc.subjectStatistics Theory
dc.titleAdaptive estimation of the transition density of a particular hidden Markov chain
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