foieGras: mpmf – R documentation

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mpmf

fit the move persistence model to regularized location data

Description

generates initial values for model parameters and unobserved gamma's; structures data and initial values for C++ TMB template; fits move persistence model; minimizes the joint log-likelihood via the selected optimizer (nlminb or optim); structures and passes output object to fit_mpm

Usage

mpmf(
  x,
  model = c("jmpm", "mpm"),
  control = mpm_control(),
  inner.control = NULL
)

Arguments

`x`	temporally regularized location data, eg. output from `fit_ssm`
`model`	specify whether MPM is to be fit with unpooled ("mpm") or pooled ("jmpm") RW variance(s).
`control`	list of control settings for the outer optimizer (see `mpm_control` for details)
`inner.control`	list of control settings for the inner optimization (see ?TMB::MakeADFUN for additional details)
`verbose`	use ssm_control(verbose = 1) instead, see `ssm_control` for details
`optim`	use ssm_control(optim = "optim") instead, see `ssm_control` for details
`optMeth`	use ssm_control(method = "L-BFGS-B") instead, see `ssm_control` for details

Details

called by fit_mpm, not intended for general use. see ?fit_mpm.

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

v0.7-6

MIT + file LICENSE

Authors

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

Initial release

2021-04-26