Bayesian Inference of the Weibull Model Based on Interval-Censored Survival Data

Joint Authors

Guure, Chris Bambey
Adam, Mohd Bakri
Ibrahim, Noor Akma

Source

Computational and Mathematical Methods in Medicine

Issue

Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-10, 10 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2013-01-10

Country of Publication

Egypt

No. of Pages

10

Main Subjects

Medicine

Abstract EN

Interval-censored data consist of adjacent inspection times that surround an unknown failure time.

We have in this paper reviewed the classical approach which is maximum likelihood in estimating the Weibull parameters with interval-censored data.

We have also considered the Bayesian approach in estimating the Weibull parameters with interval-censored data under three loss functions.

This study became necessary because of the limited discussion in the literature, if at all, with regard to estimating the Weibull parameters with interval-censored data using Bayesian.

A simulation study is carried out to compare the performances of the methods.

A real data application is also illustrated.

It has been observed from the study that the Bayesian estimator is preferred to the classical maximum likelihood estimator for both the scale and shape parameters.

American Psychological Association (APA)

Guure, Chris Bambey& Ibrahim, Noor Akma& Adam, Mohd Bakri. 2013. Bayesian Inference of the Weibull Model Based on Interval-Censored Survival Data. Computational and Mathematical Methods in Medicine،Vol. 2013, no. 2013, pp.1-10.
https://search.emarefa.net/detail/BIM-503137

Modern Language Association (MLA)

Guure, Chris Bambey…[et al.]. Bayesian Inference of the Weibull Model Based on Interval-Censored Survival Data. Computational and Mathematical Methods in Medicine No. 2013 (2013), pp.1-10.
https://search.emarefa.net/detail/BIM-503137

American Medical Association (AMA)

Guure, Chris Bambey& Ibrahim, Noor Akma& Adam, Mohd Bakri. Bayesian Inference of the Weibull Model Based on Interval-Censored Survival Data. Computational and Mathematical Methods in Medicine. 2013. Vol. 2013, no. 2013, pp.1-10.
https://search.emarefa.net/detail/BIM-503137

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-503137