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: |
ATmet, BaSTA, BVS, eiPack, hysteresis, lordif, ltm, NEff, NHMM, parfm, RM2, rriskDistributions, spatial.gev.bma, Surrogate, trioGxE |
| Reverse imports: |
Biograph, CIDnetworks, clustMD, gems, iBATCGH, optBiomarker, phytools, RMark |
| Reverse suggests: |
flexsurv, geiger, oro.pet, surveillance |