Learn R Programming

frailtyEM (version 1.0.1)

Fitting Frailty Models with the EM Algorithm

Description

Contains functions for fitting shared frailty models with a semi-parametric baseline hazard with the Expectation-Maximization algorithm. Supported data formats include clustered failures with left truncation and recurrent events in gap-time or Andersen-Gill format. Several frailty distributions, such as the the gamma, positive stable and the Power Variance Family are supported.

Copy Link

Version

Install

install.packages('frailtyEM')

Monthly Downloads

5,815

Version

1.0.1

License

GPL (>= 2)

Issues

21

Pull Requests

0

Stars

5

Forks

3

Maintainer

Theodor Balan

Last Published

September 22nd, 2019

Functions in frailtyEM (1.0.1)

Estep

Perform the E step calculations
summary.emfrail

Summary for emfrail objects
fast_Estep

Fast fitting of the E step
emfrail_control

Control parameters for emfrail
emfrail_dist

Distribution parameters for emfrail
autoplot.emfrail

Plots for emfrail objects using ggplot2
ca_test

Commenges-Andersen test for heterogeneity
predict.emfrail

Predicted hazard and survival curves from an emfrail object
residuals.emfrail

Residuals for frailty models
dist_to_pars

dist_to_pars
emfrail

Fitting semi-parametric shared frailty models with the EM algorithm
plot.emfrail

Plots for emfrail objects
logLik.emfrail

Log-likelihood for emfrail fitted models
autoplot

Generic autoplot function
emfrail_pll

Profile log-likelihood calculation
laplace_transform

Laplace transform calculation
frailtyEM-package

frailtyEM: Fitting Frailty Models with the EM Algorithm