drimmR: Estimation, Simulation and Reliability of Drifting Markov Models

Performs the drifting Markov models (DMM) which are non-homogeneous Markov models designed for modeling the heterogeneities of sequences in a more flexible way than homogeneous Markov chains or even hidden Markov models. In this context, we developed an R package dedicated to the estimation, simulation and the exact computation of associated reliability of drifting Markov models. The implemented methods are described in Vergne, N. (2008), <doi:10.2202/1544-6115.1326> and Barbu, V.S., Vergne, N. (2019) <doi:10.1007/s11009-018-9682-8> .

Version: 1.0.0
Depends: R (≥ 2.10)
Imports: seqinr, Biostrings, testthat, stats, ggplot2, parallel, future, doParallel, foreach, tidyverse, dplyr, reshape2, Rdpack
Suggests: utils, knitr, rmarkdown
Published: 2021-03-22
Author: Vlad Stefan Barbu [aut], Geoffray Brelurut [ctb], Annthomy Gilles [ctb], Arnaud Lefebvre [ctb], Corentin Lothode [aut], Victor Mataigne [ctb], Alexandre Seiller [aut], Nicolas Vergne [aut, cre]
Maintainer: Nicolas Vergne <nicolas.vergne at univ-rouen.fr>
License: GPL-3
NeedsCompilation: no
Materials: NEWS
CRAN checks: drimmR results

Downloads:

Reference manual: drimmR.pdf
Package source: drimmR_1.0.0.tar.gz
Windows binaries: r-devel: drimmR_1.0.0.zip, r-release: drimmR_1.0.0.zip, r-oldrel: drimmR_1.0.0.zip
macOS binaries: r-release: drimmR_1.0.0.tgz, r-oldrel: drimmR_1.0.0.tgz

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