Fit Continuous-Time State-Space and Latent Variable Models for
Filtering Argos Satellite (and Other) Telemetry Data and
Estimating Movement Behaviour
Fits continuous-time random walk and correlated random walk state-space models to filter 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-Methe 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 <doi:10.1002/ecy.2566>.
dplyr (>= 0.8.0), tibble (>= 2.1.3), argosfilter, ggplot2 (>=
3.0.0), gridExtra, lubridate, TMB (>= 1.7.15), sf (>= 0.8-0),
stringr, tidyr, future (>= 1.13.0), furrr (>= 0.1.0),
rworldmap, parallel
testthat, covr, knitr, rmarkdown, units, rgeos

Fit Continuous-Time State-Space and Latent Variable Models for
Quality Control of Argos Satellite (and Other) Telemetry Data
and for Estimating Movement Behaviour
c(
person(given = "Ian",
family = "Jonsen",
role = c("aut", "cre", "cph"),
email = "ian.jonsen@mq.edu.au"),
person(given = "Toby",
family = "Patterson",
role = c("aut", "ctb"),
email = "toby.patterson@cisro.au")
)
Ian Jonsen [aut, cre, cph],
Toby Patterson [aut, ctb]
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 <doi:10.1002/ecy.2566>.
tibble (>= 2.1.3), ggplot2 (>= 3.0.0), lubridate, TMB (>=
1.7.15), sf (>= 0.9-3), stringr, tidyr, future (>= 1.13.0),
furrr (>= 0.1.0), rworldmap, parallel, purrr, dplyr (>= 1.0.0),
trip, assertthat