HMMoce: Improved Analysis of Marine Animal Movement Data Using Hidden Markov Models

Improved analysis of marine animal movement data by implementing a state-space hidden Markov model (HMM) to improve position estimates. Position estimates are derived by comparing electronic tag data (from tags deployed on marine animals, typically fish) to three-dimensional oceanographic data.

Version: 1.0.0
Depends: R (≥ 2.10)
Imports: dplyr, fields, foreach, imager, locfit, lubridate, maptools, raster, RColorBrewer, rgeos, RNetCDF, sp, parallel, doParallel, curl, methods
Suggests: knitr, rmarkdown, png, grid
Published: 2017-10-29
Author: Camrin Braun [aut, cre], Benjamin Galuardi [aut], Benjamin Jones [ctb] (Contributed to earlier version of some of the download functions.), Martin Pedersen [ctb] (Developed an earlier version of some of the HMM framework and helper functions.)
Maintainer: Camrin Braun <camrin.braun at gmail.com>
BugReports: https://github.com/camrinbraun/HMMoce/issues
License: MIT + file LICENSE
URL: http://www.camrinbraun.com/
NeedsCompilation: no
Citation: HMMoce citation info
Materials: README NEWS
CRAN checks: HMMoce results

Downloads:

Reference manual: HMMoce.pdf
Vignettes: Using HMMoce
Using HMMoce
Package source: HMMoce_1.0.0.tar.gz
Windows binaries: r-devel: HMMoce_1.0.0.zip, r-release: HMMoce_1.0.0.zip, r-oldrel: HMMoce_1.0.0.zip
OS X El Capitan binaries: r-release: HMMoce_1.0.0.tgz
OS X Mavericks binaries: r-oldrel: HMMoce_1.0.0.tgz

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