A Class of Latent Markov Models for Capture–Recapture Data Allowing for Time, Heterogeneity, and Behavior Effects

DOI10.1111/j.1541-0420.2006.00702.xzbMath1134.62080OpenAlexW2090328563WikidataQ31121379 ScholiaQ31121379MaRDI QIDQ5459607

Francesco Bartolucci, Fulvia Pennoni

Publication date: 29 April 2008

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1541-0420.2006.00702.x

zbMATH Keywords

confidence intervalsEM algorithmMarkov chainlatent class modelRasch modelclosed populationsconditional maximum likelihood estimation

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Applications of statistics to environmental and related topics (62P12) Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20)

Related Items (7)

A regression estimator for mixed binomial capture-recapture data ⋮ Focused Information Criterion for Capture–Recapture Models for Closed Populations ⋮ Latent Markov models: a review of a general framework for the analysis of longitudinal data with covariates ⋮ Flexible behavioral capture-recapture modeling ⋮ A two-state mixed hidden Markov model for risky teenage driving behavior ⋮ Exploring the randomness of mentally generated head–tail sequences ⋮ Improved inference on capture recapture models with behavioural effects

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