Bayesian estimation of a competing risk model based on Weibull and exponential distributions under right censored data

TL;DR

This paper develops Bayesian methods to estimate parameters in a competing risk model combining Weibull and exponential distributions, specifically addressing challenges posed by right censored data.

Contribution

It introduces a Bayesian estimation approach for a novel competing risk model with Weibull and exponential components under right censoring.

Findings

Bayesian estimators effectively handle right censored data.

The model accurately estimates failure rates in simulated scenarios.

The approach improves upon traditional methods in reliability analysis.

Abstract

In this paper we investigate the estimation of the unknown parameters of a competing risk model based on a Weibull distributed decreasing failure rate and an exponentially distributed constant failure rate, under right censored data.likelihood estimators.