sese2

<p>Example elephant seal Argos tracking data, highly sub-sampled.
These example data are included purely to speed up examples where a fit
object is required. Generating a fit object is preferred as storing an
example fit risks GDAL errors on platforms with older GDAL libraries</p>

data

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. Track simulation functions are provided. 'Jonsen I', 'McMahon CR', 'Patterson TA', 'Auger-M<c3><a9>th<c3><a9> 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>.

Ian Jonsen

foieGras

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

Toby Patterson

sese2 function

Format

Southern elephant seal Argos satellite data (2 highly sub-sampled individuals) — sese2

Southern elephant seal Argos satellite data (2 highly sub-sampled individuals)

sese2: Southern elephant seal Argos satellite data (2 highly sub-sampled individuals)

Description

Arguments

Format