ctmcd: Estimating the Parameters of a Continuous-Time Markov Chain from Discrete-Time Data

Estimation of Markov generator matrices from discrete-time observations. The implemented approaches comprise diagonal and weighted adjustment of matrix logarithm based candidate solutions as in Israel (2001) <doi:10.1111/1467-9965.00114> as well as a quasi-optimization approach. Moreover, the expectation-maximization algorithm and the Gibbs sampling approach of Bladt and Sorensen (2005) <doi:10.1111/j.1467-9868.2005.00508.x> are included.

Version: 1.4.4
Imports: Rcpp (≥ 1.0.12), coda, expm, numDeriv
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown, R.rsp
Published: 2024-02-09
Author: Marius Pfeuffer [aut, cre], Greig Smith [ctb], Goncalo dos Reis [ctb], Linda Moestel [ctb], Matthias Fischer [ctb]
Maintainer: Marius Pfeuffer <marius.pfeuffer at fau.de>
License: GPL-3
NeedsCompilation: yes
CRAN checks: ctmcd results

Documentation:

Reference manual: ctmcd.pdf
Vignettes: A ctmcd Guide
ctmcd: An R Package for Estimating the Parameters of a Continuous-Time Markov Chain from Discrete-Time Data

Downloads:

Package source: ctmcd_1.4.4.tar.gz
Windows binaries: r-devel: ctmcd_1.4.4.zip, r-release: ctmcd_1.4.4.zip, r-oldrel: ctmcd_1.4.4.zip
macOS binaries: r-release (arm64): ctmcd_1.4.4.tgz, r-oldrel (arm64): ctmcd_1.4.4.tgz, r-release (x86_64): ctmcd_1.4.4.tgz
Old sources: ctmcd archive

Reverse dependencies:

Reverse suggests: markovchain

Linking:

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