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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 9 months ago 527 main cf201901
conda 1.0 MB | linux-64/r-msm-1.6.6-r341hc070d10_2.tar.bz2  6 years and 9 months ago 609 main cf201901
conda 1.0 MB | osx-64/r-msm-1.6.6-r341hc070d10_2.tar.bz2  6 years and 10 months ago 287 main cf201901
conda 1.4 MB | osx-64/r-msm-1.6.6-r351hc070d10_2.tar.bz2  6 years and 10 months ago 229 main cf201901
conda 1.0 MB | osx-64/r-msm-1.6.6-r341_1.tar.bz2  7 years and 2 months ago 330 main cf201901
conda 1.0 MB | linux-64/r-msm-1.6.6-r3.4.1_0.tar.bz2  7 years and 2 months ago 529 main cf201901
conda 1.0 MB | osx-64/r-msm-1.6.6-r3.4.1_0.tar.bz2  7 years and 2 months ago 226 main cf201901

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