markovchain: Easy Handling Discrete Time Markov Chains

Functions and S4 methods to create and manage discrete time Markov chains (DTMC) more easily. In addition functions to perform statistical (fitting and drawing random variates) and probabilistic (analysis of DTMC proprieties) analysis are provided.

Depends: R (≥ 3.2.0), methods
Imports: igraph, Matrix, matlab, expm, stats4, parallel, Rcpp (≥ 0.11.5), RcppParallel, utils, stats
LinkingTo: Rcpp, RcppParallel, RcppArmadillo
Suggests: knitr, testthat, diagram, DiagrammeR, msm, etm, Rsolnp, knitcitations, rmarkdown
Published: 2016-09-09
Author: Giorgio Alfredo Spedicato [aut,cre], Tae Seung Kang [aut], Sai Bhargav Yalamanchi [aut], Mildenberger Thoralf [ctb], Deepak Yadav [ctb]
Maintainer: Giorgio Alfredo Spedicato <spedicato_giorgio at>
License: GPL-2
NeedsCompilation: yes
SystemRequirements: GNU make
Citation: markovchain citation info
Materials: README NEWS ChangeLog
In views: Finance
CRAN checks: markovchain results


Reference manual: markovchain.pdf
Vignettes: An introduction to markovchain package
Complicate Steady States Analysis
Crash Introduction to markovchain R package
Package source: markovchain_0.6.5.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X Mavericks binaries: r-release: markovchain_0.6.5.1.tgz, r-oldrel: markovchain_0.6.5.1.tgz
Old sources: markovchain archive

Reverse dependencies:

Reverse imports: lifecontingencies
Reverse suggests: aqp, FuzzyStatProb


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