moveHMM — historical Pareto-support fork

Archived fork: During my MPhil research in 2018, I extended moveHMM 1.6 with Pareto Type I step-length distributions. The change covers likelihood evaluation, fitting and simulation, with the distribution parameterised by minimum step length xmin and shape mu.

This branch is preserved as a record of that contribution. It is based on an old moveHMM release and should not be used in place of the current upstream package.

The Pareto-specific implementation is in R/paretoI.R and src/densities.h, with integration through fitHMM, nLogLike, simData and the package's parameter handling. Focused regression tests are in tests/testthat/test_paretoI.R.

Upstream project

moveHMM

An R package for modelling animal movement with hidden Markov models.

Get started with the vignette: Guide to using moveHMM

Installation instructions

Stable release

The package is available on CRAN. To install it from CRAN, you can use the following commands:

# install dependencies
install.packages(c("Rcpp","RcppArmadillo","sp","CircStats"))
# install moveHMM
install.packages("moveHMM")

Install from Github

To install the latest (unstable) version of the package from Github:

install.packages(c("Rcpp","RcppArmadillo","sp","CircStats","devtools"))
library(devtools)
install_github("TheoMichelot/moveHMM", build_vignettes=TRUE)

References

Michelot, T., Langrock, R., Patterson, T.A. (2016). moveHMM: An R package for analysing animal movement data using hidden Markov models. Methods in Ecology and Evolution. 7(11), 1308-1315.

Langrock, R., King, R., Matthiopoulos, J., Thomas, L., Fortin, D., & Morales, J. M. (2012). Flexible and practical modeling of animal telemetry data: hidden Markov models and extensions. Ecology, 93(11), 2336-2342.

Patterson, T. A., Basson, M., Bravington, M. V., & Gunn, J. S. (2009). Classifying movement behaviour in relation to environmental conditions using hidden Markov models. Journal of Animal Ecology, 78(6), 1113-1123.