Title :

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

Author(s) :

Talhi, Hamida [Auteur]
Aiachi, Hiba [Auteur]
Rahmania, Nadji [Auteur]
Laboratoire Paul Painlevé - UMR 8524 [LPP]

Journal title :

Monte Carlo Methods and Applications

Pages :

163-174

Publisher :

De Gruyter

Publication date :

2022-06-01

ISSN :

0929-9629

HAL domain(s) :

Mathématiques [math]

English abstract : [en]

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 ...
Show more >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. The Bayes estimators and the corresponding risks are derived using various loss functions. Since the posterior analysis involves analytically intractable integrals, we propose a Monte Carlo method to compute these estimators. Given initial values of the model parameters, the maximum likelihood estimators are computed using the expectation-maximization algorithm. Finally, we use Pitman’s closeness criterion and integrated mean-square error to compare the performance of the Bayesian and the maximum likelihood estimators.Show less >

Language :

Anglais

Popular science :

Non

Collections :

• Laboratoire Paul Painlevé - UMR 8524

Source :

Harvested from HAL