msm: Multi-state Markov and hidden Markov models in continuous time
Functions for fitting general continuous-time Markov and
hidden Markov multi-state models to longitudinal data. 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. A variety of observation
schemes are supported, including processes observed at
arbitrary times (panel data), continuously-observed processes,
and censored states.
Downloads:
Reverse dependencies:
| Reverse depends: |
BaSTA, Biograph, BVS, CatDyn, ctarma, eiPack, geiger, lordif, ltm, parfm, RM2, surveillance |
| Reverse imports: |
optBiomarker, phytools, RMark |