SemiMarkov: Multi-States Semi-Markov Models

Functions for fitting multi-state semi-Markov models to longitudinal data. A parametric maximum likelihood estimation method adapted to deal with Exponential, Weibull and Exponentiated Weibull distributions is considered. Right-censoring can be taken into account and both constant and time-varying covariates can be included using a Cox proportional model.

Author
Agnieszka Listwon-Krol, Philippe Saint-Pierre
Date of publication
2016-01-19 09:00:08
Maintainer
Agnieszka Listwon-Krol <agnieszka.krol@isped.u-bordeaux2.fr>
License
GPL (>= 2)
Version
1.4.3

View on CRAN

Man pages

hazard
Computes hazard rates using an object of class 'semiMarkov'...
param.init
Defines the initial values of parameters for a semi-Markov...
plot.hazard
Plot method for objects of class 'hazard'
print.hazard
Print method for object of class 'hazard'
print.semiMarkov
Print method for object of class 'semiMarkov'
semiMarkov
Parametric estimation in multi-state semi-Markov models
summary.hazard
Summary method for objects of class 'hazard'
summary.semiMarkov
Summary method for objects of class 'semiMarkov'

Files in this package

SemiMarkov
SemiMarkov/inst
SemiMarkov/inst/CITATION
SemiMarkov/tests
SemiMarkov/tests/test.R
SemiMarkov/NAMESPACE
SemiMarkov/data
SemiMarkov/data/asthma.rda
SemiMarkov/R
SemiMarkov/R/SemiMarkov.r
SemiMarkov/MD5
SemiMarkov/DESCRIPTION
SemiMarkov/man
SemiMarkov/man/param.init.Rd
SemiMarkov/man/summary.semiMarkov.Rd
SemiMarkov/man/print.semiMarkov.Rd
SemiMarkov/man/semiMarkov.Rd
SemiMarkov/man/plot.hazard.Rd
SemiMarkov/man/hazard.Rd
SemiMarkov/man/summary.hazard.Rd
SemiMarkov/man/print.hazard.Rd
SemiMarkov/man/asthma.rd
SemiMarkov/man/table.state.rd