test_moissonnage_selune
type: Agent

SemiMarkov: An R Package for Parametric Estimation in Multi-State Semi-Markov Models
type: Dataset
contact point: Organization
  fn: CCSD
keyword: multi-state-semi-markov-models
keyword: mathmath-stmathematics-mathstatistics-mathst
keyword: journal-articles
keyword: infoeu-reposemanticsarticle
keyword: parametric-estimation
keyword: r-package
keyword: asthma
keyword: exponentiated-weibull-distribution
keyword: statthstatistics-statstatistics-theory-statth
landing page: 1548-7660
description: Multi-state models provide a relevant tool for studying the observations of a continuous-time process at arbitrary times. Markov models are often considered even if semi-Markov are better adapted in various situations. Such models are still not frequently applied mainly due to lack of available software. We have developed the R package SemiMarkov to fit homogeneous semi-Markov models to longitudinal data. The package performs maximum likelihood estimation in a parametric framework where the distributions of the sojourn times can be chosen between exponential, Weibull or exponentiated Weibull one. The package computes and displays the hazard rates of sojourn times and the hazard rates of the semi-Markov process. The effects of covariates can be studied with a Cox proportional hazards model for the sojourn times distributions. The number of covariates and the distribution of sojourn times can be specified for each possible transition providing a great flexibility in a model's definition. This article presents parametric semi-Markov models and gives a detailed description of the package together with an application to asthma control.
issued: 2026-05-09T19:26:01.901451
language: en
modified: 2026-05-09T19:26:01.901456

SemiMarkov: An R Package for Parametric Estimation in Multi-State Semi-Markov Models
type: Distribution
access URL: https://hal.science/hal-00860244
format: HTML
issued: 2026-05-09T19:26:01.907336
modified: 2026-05-09T19:26:01.890674