plot.predddpcomp

<p>Output an object of class predddpcomp</p>

<p>plot estimated cumulative incidence function/ subdistribution density/ subdistribution hazard functions with credible intervals of cause 1 from an object of class predddpcomp.</p>

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/right-censored/ interval-censored observations without competing risks and exact/right-censored 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. For wrapper of the DPdensity function from the R package DPpackage (already archived by CRAN) that uses the Low Information Omnibus prior, please check (<https://github.com/mjmartens/DPdensity-wrapper-with-LIO-prior>).

Yushu Shi

DPWeibull

Dirichlet Process Weibull Mixture Model for Survival Data

plot.predddpcomp function

plot estimated cumulative incidence function/ subdistribution density/ subdistribution hazard functions of cause 1 from an object of class predddpcomp. — plot.predddpcomp

plot estimated cumulative incidence function/ subdistribution density/ subdistribution hazard functions of cause 1 from an object of class predddpcomp.

plot.predddpcomp: plot estimated cumulative incidence function/ subdistribution density/ subdistribution hazard functions of cause 1 from an object of class predddpcomp.

Description

Usage

Arguments

Value