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msm (version 1.8.1)

Multi-State Markov and Hidden Markov Models in Continuous Time

Description

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.

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Install

install.packages('msm')

Monthly Downloads

24,541

Version

1.8.1

License

GPL (>= 2)

Issues

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Repository

https://github.com/chjackson/msm

Homepage

https://chjackson.github.io/msm/

Maintainer

Christopher Jackson

Last Published

October 4th, 2024

Functions in msm (1.8.1)

Developer documentation: hidden Markov model structure object

FEV1 measurements from lung transplant recipients

Developer documentation: model for covariates on misclassification probabilities

Hidden Markov model constructors

Convert a hmodel object to HMM constructor function calls

Developer documentation: misclassification model structure object

Misclassification probability matrix

Calculate tables of hazard ratios for covariates on transition intensities

Expected first passage time

Multivariate hidden Markov models

msm.form.qoutput

Extract msm model parameter estimates in compact format

Convert data for `msm' to data for `survival', `mstate' or `flexsurv' analysis

Multi-State Markov and Hidden Markov Models in Continuous Time

Fitted msm model objects

Measurement error distributions

Likelihood ratio test

Multi-state Markov and hidden Markov models in continuous time

Calculate tables of odds ratios for covariates on misclassification probabilities

Extract model log-likelihood

model.frame.msm

Extract original data from msm objects.

paramdata.object

Developer documentation: internal msm parameters object

Kaplan Meier estimates of incidence

plot.prevalence.msm

Plot of observed and expected prevalences

Exponential distribution with piecewise-constant rate

plot.survfit.msm

Plot empirical and fitted survival curves

Parameters of phase-type models in mixture form

Plots of multi-state models

pmatrix.piecewise.msm

Transition probability matrix for processes with piecewise-constant intensities

Transition probability matrix

Pearson-type goodness-of-fit test

Print a fitted msm model object

Developer documentation: model for covariates on transition intensities

Probability of each state being next

Generic function to find quantiles of a distribution

Developer documentation: transition model structure object

Transition intensity matrix

Passage probabilities

Psoriatic arthritis data

recreate.olddata

Convert data stored in msm object to old format

Summarise a fitted multi-state model

Print a fitted msm model object

Table of transitions

Simulate from a Markov model fitted using msm

Mean sojourn times from a multi-state model

Estimated ratio of transition intensities

Tables of observed and expected prevalences

Simulate multiple trajectories from a multi-state Markov model with arbitrary observation times

Explore the likelihood surface

Tidy the parameter estimates from an msm model

Tidy the output of pmatrix.msm and similar functions

tidy.msm.estbystate

Tidy the output of totlos.msm and similar functions

Truncated Normal distribution

tidy.msm.prevalence

Tidy the output of prevalence.msm

Transient and absorbing states

Score residuals

Simulate one individual trajectory from a continuous-time Markov model

Coxian phase-type distribution with two phases

Total length of stay, or expected number of visits

Update the maximum likelihood estimates in a fitted model object.

Calculate the probabilities of underlying states and the most likely path through them

Criteria for comparing two multi-state models with nested state spaces

Developer documentation: censoring model object

Extract model coefficients

The delta method

Matrix exponential

Bootstrap resampling for multi-state models

Aortic aneurysm progression data

Heart transplant monitoring data

Calculate crude initial values for transition intensities

Bronchiolitis obliterans syndrome after lung transplants