msm: Multi-State Markov and Hidden Markov Models in Continuous Time

Functions for fitting continuous-time Markov and hidden Markov multi-state models to longitudinal data. Designed for processes observed at arbitrary times in continuous time (panel data) but some other observation schemes are supported. Both Markov transition rates and the hidden Markov output process can be modelled in terms of covariates, which may be constant or piecewise-constant in time.

Version: 1.6
Imports: survival, mvtnorm, expm
Suggests: mstate, minqa, doParallel, foreach, numDeriv, testthat, flexsurv
Published: 2015-11-18
Author: Christopher Jackson
Maintainer: Christopher Jackson <chris.jackson at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: msm citation info
Materials: NEWS ChangeLog
In views: Distributions, Survival
CRAN checks: msm results


Reference manual: msm.pdf
Vignettes: User guide to msm with worked examples
Package source: msm_1.6.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X Snow Leopard binaries: r-release: msm_1.5.tgz, r-oldrel: msm_1.5.tgz
OS X Mavericks binaries: r-release: msm_1.6.tgz
Old sources: msm archive

Reverse dependencies:

Reverse depends: ATmet, BVS, CEoptim, eiPack, hysteresis, ltm, NEff, NHMM, RM2, score, spatial.gev.bma, Surrogate, trioGxE
Reverse imports: breakpoint, CIDnetworks, clustMD, decisionSupport, drLumi, gems, gmnl, httk, iBATCGH, optBiomarker, parfm, phytools, Rchoice, RMark, rriskDistributions, rtdists, sparsereg, TAM
Reverse suggests: flexsurv, markovchain,, surveillance