aniMotum - Fit Continuous-Time State-Space and Latent Variable Models for Quality Control of Argos Satellite (and Other) Telemetry Data and for Estimating Changes in Animal Movement

Fits continuous-time random walk, correlated random walk and move persistence state-space models for location estimation and behavioural inference from animal tracking data ('Argos', processed light-level 'geolocation', 'GPS'). Template Model Builder ('TMB') is used for fast random-effects estimation. The 'Argos' data can be: (older) least squares-based locations; (newer) Kalman filter-based locations with error ellipse information; or a mixture of both. The models estimate two sets of location states corresponding to: 1) each observation, which are (usually) irregularly timed; and 2) user-specified time intervals (regular or irregular). A track re-routing function is provided to adjust location estimates for known movement barriers. Track simulation functions are provided. Latent variable models are also provided to estimate move persistence from track data not requiring state-space model filtering.

Last updated 2 days ago

animal-movementanimal-trackingrandom-effects-modelstate-space-modelstmbcpp

7.23 score 39 stars 59 scripts

bsam - Bayesian State-Space Models for Animal Movement

Tools to fit Bayesian state-space models to animal tracking data. Models are provided for location filtering, location filtering and behavioural state estimation, and their hierarchical versions. The models are primarily intended for fitting to ARGOS satellite tracking data but options exist to fit to other tracking data types. For Global Positioning System data, consider the 'moveHMM' package. Simplified Markov Chain Monte Carlo convergence diagnostic plotting is provided but users are encouraged to explore tools available in packages such as 'coda' and 'boa'.

Last updated 7 months ago

cran-downloadsjagscpp

5.42 score 17 stars 31 scripts 603 downloads

simfish - simulate fish tracks & acoustic detections

facilitates simulation of fish tracks in featureless and semi-realistic environments (coastal oceans, fjords, and lakes). A user-defined raster defining the water body - land boundaries is used to constrain simulated tracks. Fish movements are simulated (currently) as either a correlated random walk or a biased & correlated random walk, with the bias toward a defined Centre-of-Attraction. A potential function is used to ensure the tracks avoid land. The package can also be used to simulate detections of acoustically-tagged fish by acoustic receivers at user-defined locations.

Last updated 1 years ago

2.70 score 3 scripts