Edgeworth expansion for \(M\)-estimators of \(V\)-geometrically ergodic Markov chains

DOI10.1016/J.CRMA.2010.02.009zbMath1186.62103OpenAlexW2029813248MaRDI QIDQ961013

Déborah Ferré

Publication date: 29 March 2010

Published in: Comptes Rendus. Mathématique. Académie des Sciences, Paris (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.crma.2010.02.009

Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20) Markov processes: estimation; hidden Markov models (62M05)

Related Items (2)

Limit theorems for stationary Markov processes with \(L^{2}\)-spectral gap ⋮ Parametric first-order Edgeworth expansion for Markov additive functionals. Application to \(M\)-estimations

Cites Work

• Markov chains and stochastic stability
• Étude de l'estimateur du maximum de vraisemblance dans le cas d'un processus autorégressif: convergence, normalité asymptotique, vitesse de convergence. (Asymptotic behaviour of maximum likelihood estimator in an autoregressive process: consistency, asymptotic distribution and expansion, rate of convergence)
• Asymptotic expansions related to minimum contrast estimators
• ON LIKELIHOOD ESTIMATION FOR DISCRETELY OBSERVED MARKOV JUMP PROCESSES

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