Combining a Bayesian nonparametric method with a hierarchical framework to estimate individual and temporal variation in growth

Ecological Modelling

Volumn 247, Issue , 2012, Pages 125-134

  Sigourney, Douglas B ^a,c   Munch, Stephan B ^b   Letcher, Benjamin H ^c  

^a UNIVERSITY OF MASSACHUSETTS   (United States)

^b SOUTHWEST FISHERIES SCIENCE CENTER   (United States)

^c U S GEOLOGICAL SURVEY   (United States)

Author keywords

Atlantic salmon; Bayesian state space model; Gaussian process; Growth model; Mark recapture; Random effects

Indexed keywords

ATLANTIC SALMON; GAUSSIAN PROCESSES; GROWTH MODELS; MARK-RECAPTURE; RANDOM EFFECTS; STATE SPACE MODEL;

CONSERVATION; DYNAMICS; ESTIMATION; GAUSSIAN DISTRIBUTION; GAUSSIAN NOISE (ELECTRONIC); STATE SPACE METHODS;

PARAMETER ESTIMATION;

BAYESIAN ANALYSIS; DATA SET; GAUSSIAN METHOD; GROWTH MODELING; GROWTH RATE; HIERARCHICAL SYSTEM; INDIVIDUAL VARIATION; JUVENILE; MARK-RECAPTURE METHOD; NUMERICAL MODEL; SALMONID; SEASONALITY; TEMPORAL VARIATION;

SALMO SALAR;

EID: 84866273514     PISSN: 03043800     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ecolmodel.2012.08.009     Document Type: Article

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