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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.

Type Size Name Uploaded Downloads Labels
conda 1.4 MB | linux-64/r-msm-1.6.6-r351hc070d10_2.tar.bz2  6 years and 3 months ago 446 main cf201901
conda 1.0 MB | linux-64/r-msm-1.6.6-r341hc070d10_2.tar.bz2  6 years and 3 months ago 545 main cf201901
conda 1.0 MB | osx-64/r-msm-1.6.6-r341hc070d10_2.tar.bz2  6 years and 3 months ago 272 main cf201901
conda 1.4 MB | osx-64/r-msm-1.6.6-r351hc070d10_2.tar.bz2  6 years and 3 months ago 214 main cf201901
conda 1.0 MB | osx-64/r-msm-1.6.6-r341_1.tar.bz2  6 years and 7 months ago 318 main cf201901
conda 1.0 MB | linux-64/r-msm-1.6.6-r3.4.1_0.tar.bz2  6 years and 7 months ago 471 main cf201901
conda 1.0 MB | osx-64/r-msm-1.6.6-r3.4.1_0.tar.bz2  6 years and 7 months ago 212 main cf201901

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