Use Dirichlet process Weibull mixture model and dependent Dirichlet process Weibull mixture model for survival data with and without competing risks. Dirichlet process Weibull mixture model is used for data without covariates and dependent Dirichlet process model is used for regression data. The package is designed to handle exact/rightcensored/ intervalcensored observations without competing risks and exact/rightcensored observations for data with competing risks. Inside each cluster of Dirichlet process, we assume a multiplicative effect of covariates as in Cox model and Fine and Gray model. In addition, we provide a wrapper for DPdensity() function from the R package 'DPpackage'. This wrapper automatically uses Low Information Omnibus prior and can model one and two dimensional data with Dirichlet mixture of Gaussian distributions.
Package details 


Author  Yushu Shi, Michael Martens 
Date of publication  20180322 08:29:52 UTC 
Maintainer  Yushu Shi <[email protected]> 
License  GPL (>= 2) 
Version  1.2 
Package repository  View on CRAN 
Installation 
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