argos_lc

<p>number of location class values to be randomly sampled</p>

<p>uses data from: 1) all IMOS reprocessed KF data (2012 - 2015);
2) LESE, SESE, HBTU KF data in Jonsen et al. 2020 Move Ecol to specify
Argos location quality class proportions</p>

internal

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

argos_lc: simulate Argos error classes for LS data

Description

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