On an optimal asymptotic property of the maximum likelihood estimator of a parameter from a stochastic process

DOI10.1016/0304-4149(78)90064-9zbMath0387.62068OpenAlexW2006179883MaRDI QIDQ1249915

Christopher C. Heyde

Publication date: 1978

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

Full work available at URL: https://doi.org/10.1016/0304-4149(78)90064-9

Mathematics Subject Classification ID

Markov processes: estimation; hidden Markov models (62M05) Branching processes (Galton-Watson, birth-and-death, etc.) (60J80)

Related Items (9)

Asymptotic tests of composite hypotheses for non-ergodic type stochastic processes ⋮ Asymptotic inference for stochastic processes ⋮ Asymptotically minimax tests of composite hypotheses for nonergodic type processes ⋮ Unnamed Item ⋮ ON THE ASYMPTOTIC EFFICIENCY OF ESTIMATORS OF THE PARAMETERS OF AN ARMA PROCESS ⋮ On estimator efficiency in stochastic processes ⋮ A note on asymptotic inference in a class of non-stationary processes ⋮ Maximum likelihood estimation in branching process with continuous state space ⋮ Recursive identification in continuous-time stochastic processes

Cites Work

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• A central limit theorem for martingales and an application to branching processes
• Martingale invariance principles
• Dependent central limit theorems and invariance principles
• Certain properties of the generalized power series distribution
• Remarks on efficiency in estimation for branching processes
• Some Simple Conditions for Limit Theorems to Be Mixing
• Generalized Maximum Likelihood Estimators
• Extension of a Result of Seneta for the Super-Critical Galton-Watson Process
• Contiguity of Probability Measures
• Branching Processes

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