benaug/move.HMM: Fit HMM and HSMM animal movement models

move.HMM is used to fit hidden Markov models , allowing for multiple observation variables with different distributions. Models can be compared via AICc and fit can be assessed by plotting the fitted models, ordinary normal pseudoresiduals, and goodness-of-fit plots introduced by Altman (2004). Conditional state probabilities can be calculated and global decoding can be performed via the Viterbi algorithm. Support for Rcpp is inlcluded which can greatly speed up fitting HMMs to longer time series and HSMMs, generally. The package was developed for inferring behavioral states from animal movement and sensor data, but is more widely applicable.

Getting started

Package details

AuthorBen Augustine and Roland Langrock
Maintainer<[email protected]>
LicenseWhat license is it under?
Version1.0
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("benaug/move.HMM")
benaug/move.HMM documentation built on May 11, 2017, 4:15 a.m.