Bayesian Parameter Estimation and Model Selection for Gallbladder Cancer Data of two Countries

Authors

Richa Srivastava, Jaipuria Institute of Management, Lucknow, IndiaFollow
Rakesh Ranjan, DST-Center of Interdisciplinary Mathematical Sciences (CIMS), Banaras Hindu University, IndiaFollow
Himanshu Misra, Jaipuria Institute of Management, Lucknow, IndiaFollow

Abstract

The paper proposes statistical model and complete Bayesian inference for cancer survival data of two countries. Complete posterior analysis is done by generating random samples from posterior surface. Gibbs sampler, Markov chain Monte Carlo (MCMC)method has been used, for generating samples from posterior distribution. The paper also provides algorithm for Gibbs sampler generation scheme for proposed model parameters as well its density estimation. Model compatibility and inter model comparisons, using the measures of Bayesian information criterion (BIC) and deviance information criterion (DIC) has been used.

Digital Object Identifier (DOI)

http://dx.doi.org/10.18576/jsap/110119

Recommended Citation

Srivastava, Richa; Ranjan, Rakesh; and Misra, Himanshu (2022) "Bayesian Parameter Estimation and Model Selection for Gallbladder Cancer Data of two Countries," Journal of Statistics Applications & Probability: Vol. 11: Iss. 1, Article 19.
DOI: http://dx.doi.org/10.18576/jsap/110119
Available at: https://digitalcommons.aaru.edu.jo/jsap/vol11/iss1/19