CRAN/E | momentuHMM

momentuHMM

Maximum Likelihood Analysis of Animal Movement Behavior Using Multivariate Hidden Markov Models

Installation

About

Extended tools for analyzing telemetry data using generalized hidden Markov models. Features of momentuHMM (pronounced “momentum”) include data pre-processing and visualization, fitting HMMs to location and auxiliary biotelemetry or environmental data, biased and correlated random walk movement models, hierarchical HMMs, multiple imputation for incorporating location measurement error and missing data, user-specified design matrices and constraints for covariate modelling of parameters, random effects, decoding of the state process, visualization of fitted models, model checking and selection, and simulation. See McClintock and Michelot (2018) doi:10.1111/2041-210X.12995.

Citation momentuHMM citation info
github.com/bmcclintock/momentuHMM
github.com/bmcclintock/momentuHMM/discussions
Bug report File report

Key Metrics

Version 1.5.5
R ≥ 2.10
Published 2022-10-18 556 days ago
Needs compilation? yes
License GPL-3
CRAN checks momentuHMM results

Downloads

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Last 7 days 78 -30%
Last 30 days 531 -19%
Last 90 days 1.661 -5%
Last 365 days 6.490 -17%

Maintainer

Maintainer

Brett McClintock

brett.mcclintock@noaa.gov

Authors

Brett McClintock
Theo Michelot

Material

README
NEWS
Reference manual
Package source

In Views

MissingData
SpatioTemporal
Tracking

Vignettes

Guide to using momentuHMM

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

momentuHMM archive

Depends

R ≥ 2.10

Imports

Rcpp
doParallel
foreach
numDeriv
CircStats
crawl ≥2.2.1
mvtnorm
sp
MASS
Brobdingnag
doRNG
rlang
raster

Suggests

testthat
setRNG
splines
splines2 ≥ 0.2.8
R.rsp
conicfit
ggplot2
ggmap
lubridate
dplyr
magrittr
scatterplot3d
BB
expm
matrixcalc
moveHMM
extraDistr
data.tree ≥ 1.0.0
geosphere
mitools
doFuture
future
car
survival
prodlim
nleqslv
qdapRegex

LinkingTo

Rcpp
RcppArmadillo