smcure: An R-package for estimating semiparametric mixture cure models

frailtyEM: An R Package for Estimating Semiparametric Shared Frailty Models

When analyzing correlated time to event data, shared frailty (random effect) models are particularly attractive. However, the estimation of such models has proved challenging. In semiparametric models, this is further complicated by the presence of the nonparametric baseline hazard. Although recent years have seen an increased availability of software for fitting frailty models, most software p...

A SAS macro for parametric and semiparametric mixture cure models

Cure models have been developed to analyze failure time data with a cured fraction. For such data, standard survival models are usually not appropriate because they do not account for the possibility of cure. Mixture cure models assume that the studied population is a mixture of susceptible individuals, who may experience the event of interest, and non-susceptible individuals that will never ex...

mixtools: An R Package for Analyzing Finite Mixture Models

The mixtools package for R provides a set of functions for analyzing a variety of finite mixture models. These functions include both traditional methods, such as EM algorithms for univariate and multivariate normal mixtures, and newer methods that reflect some recent research in finite mixture models. In the latter category, mixtools provides algorithms for estimating parameters in a wide rang...

GGMselect: R package for estimating Gaussian graphical models

BayesMix: An R package for Bayesian Mixture Modeling

The R package BayesMix provides the functionality for estimating univariate Gaussian mixture models with MCMC methods. Within a given model class users can modify the prior specifications and the initial values for developing a suitable model for their data. Furthermore, tools for analyzing the output of the MCMC simulations as, e.g., diagnostic plots, are available. The package is intended to ...