Mixture models for type II censored survival data in the presence of covariates

被引：0

作者：

Jorge Alberto Achcar

Gilberto de Araújo Pereira

机构：

[1] Universidade de São Paulo,Instituto de Ciências Matemáticas e de Computação

[2] Faculdade de Medicina do Triângulo Mineiro-FMTM,Departamento de Enfermagem em Saúde Comunitária

来源：

Computational Statistics | 1999年 / 14卷

关键词：

Mixture models; regression analysis; Bayesian analysis; Gibbs samples; Metropolis-Hastings algorithm;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

In this paper, we present a Bayesian analysis of mixture models for survival data in the presence of one covariate, and type II censoring data. Considering Gibbs with Metropolis-Hastings algorithms, we get Monte Carlo estimates for the posterior quantities of interest, assuming different choices for the densities in the mixture model. We introduce a numerical example, to illustrate the proposed methodology.

引用

页码：233 / 250

页数：17

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