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. A
variety of observation schemes are supported, including
processes observed at arbitrary times (panel data),
continuously-observed processes, and censored states. 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.
Downloads:
Reverse dependencies:
| Reverse depends: |
BaSTA, Biograph, bscr, BVS, CatDyn, ctarma, eiPack, geiger, lordif, ltm, parfm, RM2, RMark, rriskDistributions, trioGxE |
| Reverse imports: |
gems, optBiomarker, phytools |
| Reverse suggests: |
oro.pet, surveillance |