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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 2 months ago 445 main cf201901
conda 1.0 MB | linux-64/r-msm-1.6.6-r341hc070d10_2.tar.bz2  6 years and 2 months ago 544 main cf201901
conda 1.0 MB | osx-64/r-msm-1.6.6-r341hc070d10_2.tar.bz2  6 years and 3 months ago 271 main cf201901
conda 1.4 MB | osx-64/r-msm-1.6.6-r351hc070d10_2.tar.bz2  6 years and 3 months ago 213 main cf201901
conda 1.0 MB | osx-64/r-msm-1.6.6-r341_1.tar.bz2  6 years and 7 months ago 317 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 470 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 211 main cf201901

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