A class of latent Markov models for capture-recapture data allowing for time, heterogeneity, and behavior effects

Biometrics

Volumn 63, Issue 2, 2007, Pages 568-578

  Bartolucci, Francesco ^a   Pennoni, Fulvia ^b  

^a UNIVERSITY OF PERUGIA   (Italy)

^b UNIVERSITY OF MILANO BICOCCA   (Italy)

Author keywords

Closed populations; Conditional maximum likelihood estimation; Confidence intervals; EM algorithm; Latent class model; Markov chain; Rasch model

Indexed keywords

CHAINS; MARKOV PROCESSES; POPULATION STATISTICS;

CAPTURE-RECAPTURE; CLOSED POPULATION; CONDITIONAL MAXIMUM LIKELIHOOD ESTIMATION; CONDITIONAL MAXIMUM LIKELIHOODS; CONFIDENCE INTERVAL; EM ALGORITHMS; LATENT CLASS MODEL; MAXIMUM-LIKELIHOOD ESTIMATION; RASCH MODELING; TRANSITION PROBABILITIES;

MAXIMUM LIKELIHOOD ESTIMATION;

ALGORITHM; CAPTURE METHOD; DATA SET; ESTIMATION METHOD; HETEROGENEITY; MAMMAL; MARKOV CHAIN; POPULATION SIZE;

ALGORITHM; ARTICLE; CONFIDENCE INTERVAL; DATA ANALYSIS; MAXIMUM LIKELIHOOD METHOD; POPULATION SIZE; PROBABILITY; RASCH ANALYSIS; STATISTICAL ANALYSIS; STATISTICAL PARAMETERS;

MAMMALIA;

EID: 34547679632     PISSN: 0006341X     EISSN: 15410420     Source Type: Journal    
DOI: 10.1111/j.1541-0420.2006.00702.x     Document Type: Article

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