Monte carlo inference for state-space models of wild animal populations

Biometrics

Volumn 65, Issue 2, 2009, Pages 572-583

  Newman, Ken B ^a,c   Fernández, Carmen ^b   Thomas, Len ^a   Buckland, Stephen T ^a  

^a UNIVERSITY OF ST ANDREWS   (United Kingdom)

^b INSTITUTO ESPAÑOL DE OCEANOGRAFÍA   (Spain)

^c U S FISH AND WILDLIFE SERVICE   (United States)

Author keywords

Auxiliary particle filter; British grey seals; Chinook salmon; Markov chain Monte Carlo; Parameter kernel smoothing; Rejection control; Sequential importance sampling

Indexed keywords

ANIMALS; BANDPASS FILTERS; BAYESIAN NETWORKS; IMPORTANCE SAMPLING; MARKOV PROCESSES; POPULATION STATISTICS; STATE SPACE METHODS;

AUXILIARY PARTICLE FILTER; BRITISH GRAY SEAL; CHINOOK SALMON; GREY SEAL; KERNEL SMOOTHING; MARKOV CHAIN MONTE CARLO; MARKOV CHAIN MONTE-CARLO; PARAMETER KERNEL SMOOTHING; REJECTION CONTROLS; SEQUENTIAL IMPORTANCE SAMPLING;

CHAINS;

BAYESIAN ANALYSIS; COMPARATIVE STUDY; METAPOPULATION; MODELING; MONTE CARLO ANALYSIS; PINNIPED; POPULATION MODELING; SALMONID; SAMPLING; TEMPORAL DISTRIBUTION; WILD POPULATION;

ALGORITHM; ARTICLE; BAYES THEOREM; CONTROLLED STUDY; EXPERIMENTAL MODEL; MATHEMATICAL PARAMETERS; METAPOPULATION; MONTE CARLO METHOD; NONHUMAN; OBSERVATIONAL METHOD; ONCORHYNCHUS TSHAWYTSCHA; PROBABILITY; SAMPLE SIZE; SAMPLING; SEAL; SIMULATION; WILD ANIMAL;

ANIMALIA; HALICHOERUS GRYPUS; ONCORHYNCHUS TSHAWYTSCHA;

EID: 66949133100     PISSN: 0006341X     EISSN: 15410420     Source Type: Journal    
DOI: 10.1111/j.1541-0420.2008.01073.x     Document Type: Article

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