Asymptotic inference for Markov step processes: Observation up to a random time

DOI10.1016/0304-4149(93)90049-AzbMath0813.62074OpenAlexW2012066472MaRDI QIDQ1312304

Reinhard Hoepfner

Publication date: 17 February 1994

Published in: Stochastic Processes and their Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0304-4149(93)90049-a

zbMATH Keywords

local asymptotic normalitymaximum likelihood estimatorlocal asymptotic mixed normalityLANconvolution theoremhomogeneity assumptionlocal asymptotic quadraticityLAMNbounded stopping timesLAQMarkov step processinformation processes

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Markov processes: estimation; hidden Markov models (62M05) Stopping times; optimal stopping problems; gambling theory (60G40)

Related Items (4)

Nonparametric estimators for Markov step processes ⋮ Local asymptotic quadraticity of stochastic process models based on stopping times ⋮ Optimality of estimators for misspecified semi-Markov models ⋮ On non-parametric estimation of the Lévy kernel of Markov processes

Cites Work

• Asymptotic conditional inference for regular nonergodic models with an application to autoregressive processes
• Asymptotic optimal inference for non-ergodic models
• Mathematical theory of statistics. Statistical experiments and asymptotic decision theory
• On the strong approximation of the distributions of estimators in linear stochastic models, I and II: Stationary and explosive AR models
• On the Hellinger type distances for filtered experiments
• Some asymptotic results for the branching process with immigration
• Asymptotics in statistics: some basic concepts
• Asymptotic ancillarity and conditional inference for stochastic processes
• Local asymptotic mixed normality for semimartingale experiments
• On statistics of Markov step processes: Representation of log-likelihood ratio processes in filtered local models
• Asymptotic minimax results for stochastic process families with critical points
• Maximum likelihood estimation in the birth-and-death process
• Convergence of filtered statistical models and Hellinger processes
• Local asymptotic normality and mixed normality for Markov statistical models
• The critical branching process with immigration stopped at zero
• Asymptotic minimaxity of a sequential estimator for a first order autoregressive model
• Multivariate point processes: predictable projection, Radon-Nikodym derivatives, representation of martingales
• A characterization of limiting distributions of regular estimates
• On the critical Galton-Watson process with immigration
• Life-Periods of a Branching Process with Immigration
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