Bayesian Survival Analysis of Generalized DUS Exponential Distribution

Austrian Journal of Statistics

article

Mohammed H AbuJarad¹  Athar Ali Khan¹  Eman S A AbuJarad² 

[1] Aligarh Muslim University, Department of Statistics and Operations Research;Aligarh Muslim University, Department of Mathematics

关键词: GDUSED;    LaplaceApproximation;    LaplacesDemon;    posterior;    survival function;    hazard function;    simulation;    Bayesian inference;    JAGS;    R.;   

DOI  :  10.17713/ajs.v49i5.927

学科分类：医学（综合）

来源: Austrian Statistical Society

【 摘 要 】

Modeling and analysis of survival rate has proved a fruitful aspect of statistical work in many fields of science. This paper aims at using a Bayesian approach to tting generalized DUS Exponential distribution (GDUSED). Kumar et al. (2015) proposed a renovation and called it DUS transformation. A Bayesian approach has been assumed to fit this model as a survival model. A real survival data set is used for illustration. Implementation is done using LaplaceApproximation and JAGS. Some graphical representations related to the probability density function and hazard function of the (GDUSED) are provided. LaplaceApproximation and JAGS codes have been provided to implement a censoring mechanism using both optimization and simulation tools.

【 授权许可】

CC BY