Sur la convergence du processus de vraisemblance en variables markoviennes

DOI10.1007/BF00532593zbMath0519.60031MaRDI QIDQ3668576

No author found.

Publication date: 1983

Published in: Zeitschrift für Wahrscheinlichkeitstheorie und verwandte Gebiete (Search for Journal in Brave)

zbMATH Keywords

conditional informationweak convergence of likelihood functions

Mathematics Subject Classification ID

Convergence of probability measures (60B10) Functional limit theorems; invariance principles (60F17)

Related Items (1)

Local asymptotic normality and mixed normality for Markov statistical models

Cites Work

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• The weak convergence of the likelihood ratio random fields for Markov observations
• On Sequential Estimation under the Conditions of Local Asymptotic Normality
• On the Behavior of Generalized Bayes Estimators for Markov Observations
• Asymptotic distribution of the log-likelihood function for stochastic processes
• Asymptotic Behavior of Statistical Estimators in the Smooth Case. I. Study of the Likelihood Ratio
• Contiguity of Probability Measures
• On the Assumptions Used to Prove Asymptotic Normality of Maximum Likelihood Estimates

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