Estimating the transition probabilities from censored Markov renewal processes

DOI10.1016/0167-7152(90)90110-SzbMath0714.62072OpenAlexW2024537500MaRDI QIDQ751136

Michael J. Phelan

Publication date: 1990

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0167-7152(90)90110-s

zbMATH Keywords

consistencyasymptotic normalityMarkov renewal processMarkov chainGaussian random variablescensored observationsestimating the transition probabilitiesmartingale estimators

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Markov processes: estimation; hidden Markov models (62M05)

Related Items (3)

Efficient Estimation for Semiparametric Semi-Markov Processes ⋮ Bayesian nonparametric estimation for reinforced Markov renewal processes ⋮ Estimation with right-censored observations under a semi-Markov model

Cites Work

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• Inference from censored Markov chains with applications to multiwave panel data
• Nonparametric estimation based on censored observations of a Markov renewal process
• The Existence and Uniqueness of Stationary Measures for Markov Renewal Processes

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