mpmf: fit the move persistence model to regularized location data

In ianjonsen/foieGras: Fit Continuous-Time State-Space and Latent Variable Models for Quality Control of Argos Satellite (and Other) Telemetry Data and for Estimating Changes in Animal Movement

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	is deprecated, use ssm_control(verbose = 1) instead, see ssm_control for details
optim	is deprecated, use ssm_control(optim = "optim") instead, see ssm_control for details
optMeth	is deprecated, 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.

ianjonsen/foieGras documentation built on Jan. 17, 2025, 11:15 p.m.