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

Fits continuous-time random walk and correlated random walk state-space models for quality control animal tracking data ('Argos', processed light-level 'geolocation', 'GPS'). Template Model Builder ('TMB') is used for fast 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). Latent variable models are provided to estimate move persistence along tracks as an index of behaviour. 'Jonsen I', 'McMahon CR', 'Patterson TA', 'Auger-Méthé M', 'Harcourt R', 'Hindell MA', 'Bestley S' (2019) Movement responses to environment: fast inference of variation among southern elephant seals with a mixed effects model. Ecology 100:e02566 .


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0.6-9 by Ian Jonsen, 2 months ago


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Authors: Ian Jonsen [aut, cre, cph] , Toby Patterson [aut, ctb]

Documentation:   PDF Manual  

Task views: Handling and Analyzing Spatio-Temporal Data, Processing and Analysis of Tracking Data

MIT + file LICENSE license

Imports tibble, ggplot2, lubridate, TMB, sf, stringr, tidyr, future, furrr, rworldmap, parallel, purrr, dplyr, trip, assertthat, wesanderson, patchwork

Suggests testthat, covr, knitr, rmarkdown, rgeos

Linking to TMB, RcppEigen

System requirements: C++11, GDAL (>= 2.4.2), GEOS (>= 3.7.0), PROJ (>= 5.2.0)

See at CRAN