Models provided are DCRW (for location filtering), DCRWS (for
location filtering and behavioural state estimation), and their hierarchical
versions (hDCRW, hDCRWS) to estimate parameters jointly across multiple
individual tracking datasets. The models are fit in JAGS using Markov chain
Monte Carlo simulation methods. The models are intended to be fit to Argos
satellite tracking data but options exist to allow fits to other tracking
data types (type
?fit_ssm for details).
Fit Bayesian state-space models to Argos satellite tracking data. Models provided are DCRW - for location filtering; DCRWS - for location filtering and behavioural state estimation with 2 behavioural states; hDCRW and hDCRWS - hierarchical models for location filtering only, and location filtering with behavioural state estimation, respectively, across multiple animals.
The hierarchical models may provide improved location and/or behavioural state estimates compared to fitting DCRW/DCRWS to individual datasets.
Maintainer: Ian Jonsen <email@example.com>
Jonsen ID, Mills Flemming J, Myers RA (2005) Robust state-space modeling of animal movement data. Ecology 86:2874-2880
Jonsen ID (2016) Joint estimation over multiple individuals improves behavioural state inference from animal movement data. Scientific Reports 6:20625
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Loading required package: rjags Loading required package: coda Linked to JAGS 4.3.0 Loaded modules: basemod,bugs Attaching package: ‘bsam’ The following object is masked from ‘package:stats’: simulate module dic loaded Compiling data graph Resolving undeclared variables Allocating nodes Initializing Reading data back into data table Compiling model graph Resolving undeclared variables Allocating nodes Graph information: Observed stochastic nodes: 808 Unobserved stochastic nodes: 192 Total graph size: 7220 Initializing model NOTE: Stopping adaptation Elapsed time: 0.07 min
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