Parametric first-order Edgeworth expansion for Markov additive functionals. Application to \(M\)-estimations

DOI10.1214/13-AIHP592zbMath1322.60158OpenAlexW2080552484MaRDI QIDQ2346196

Déborah Ferré

Publication date: 29 May 2015

Published in: Annales de l'Institut Henri Poincaré. Probabilités et Statistiques (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.aihp/1428672691

zbMATH Keywords

additive functionalsergodic Markov chainEdgeworth expansionperturbation operator\(M\)-estimations

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Central limit and other weak theorems (60F05) Markov processes: estimation; hidden Markov models (62M05) Discrete-time Markov processes on general state spaces (60J05) Local time and additive functionals (60J55)

Cites Work

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• A uniform Berry-Esseen theorem on \(M\)-estimators for geometrically ergodic Markov chains
• Limit theorems for stationary Markov processes with \(L^{2}\)-spectral gap
• Efficient likelihood estimation in state space models
• Markov chains and stochastic stability
• Efficient parameter estimation for self-similar processes
• Edgeworth expansion for \(M\)-estimators of \(V\)-geometrically ergodic Markov chains
• Maximum likelihood estimation for Markov processes
• On the approximation of positive operators and the behaviour of the spectra of the approximants
• Valid asymptotic expansions for the maximum likelihood estimators of the parameter of a stationary, Gaussian, strongly dependent process
• Asymptotic distribution of statistics in time series
• A renewal approach to Markovian \(U\)-statistics
• Asymptotic expansions related to minimum contrast estimators
• Note on minimum contrast estimates for Markov processes
• The Nagaev-Guivarc’h method via the Keller-Liverani theorem
• Regenerative stochastic processes
• ON LIKELIHOOD ESTIMATION FOR DISCRETELY OBSERVED MARKOV JUMP PROCESSES
• Approximations for densities of sufficient estimators
• [https://portal.mardi4nfdi.de/wiki/Publication:3933699 The Berry-Esse�n theorem for strongly mixing Harris recurrent Markov chains]
• Asymptotic Inference in Markov Processes

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