Asymptotic inference for continuous-time Markov chains

DOI10.1007/BF00959616zbMath0627.62086OpenAlexW2039707935MaRDI QIDQ1092575

Reinhard Hoepfner

Publication date: 1988

Published in: Probability Theory and Related Fields (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf00959616

zbMATH Keywords

continuous-time Markov chains

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Asymptotic distribution theory in statistics (62E20) Markov processes: estimation; hidden Markov models (62M05)

Related Items (2)

Nonparametric estimators for Markov step processes ⋮ Local asymptotic normality and mixed normality for Markov statistical models

Cites Work

• Cox's regression model for counting processes: A large sample study
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• Point processes and queues. Martingale dynamics
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• The Integral of a Symmetric Unimodal Function over a Symmetric Convex Set and Some Probability Inequalities
• Parametric inference in Markov branching processes with time-dependent random immigration rate
• Central limit theorems for local martingales
• Criteria for ergodicity, exponential ergodicity and strong ergodicity of Markov processes
• A Functional Central Limit Theorem for Semimartingales
• Multivariate point processes: predictable projection, Radon-Nikodym derivatives, representation of martingales
• Weak convergence of stochastic integrals related to counting processes
• The Lindeberg-Levy Theorem for Martingales
• Some Conditions for Ergodicity and Recurrence of Markov Chains
• A characterization of limiting distributions of regular estimates
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