Variational bayesian inference for exponentiated weibullright-censored survnaldata

The Weibull, log-logistic and log-normal distributions represent the heavy-tailed distributions that are often used in modelling time-to-event data. While the loglogistic and log-normal distributions are mainly used for modelling unimodal hazard functions, the Weibull distribution is well-known f...

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Main Author:	Abubakar, Jibril
Format:	Thesis
Language:	English English English
Published:	2023
Subjects:	T Technology (General)
Online Access:	http://eprints.uthm.edu.my/10976/1/24p%20JIBRIL%20ABUBAKAR.pdf http://eprints.uthm.edu.my/10976/2/JIBRIL%20ABUBAKAR%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/10976/3/JIBRIL%20ABUBAKAR%20WATERMARK.pdf
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id	my-uthm-ep.10976
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spelling	my-uthm-ep.109762024-05-15T07:26:15Z Variational bayesian inference for exponentiated weibullright-censored survnaldata 2023-09 Abubakar, Jibril T Technology (General) The Weibull, log-logistic and log-normal distributions represent the heavy-tailed distributions that are often used in modelling time-to-event data. While the loglogistic and log-normal distributions are mainly used for modelling unimodal hazard functions, the Weibull distribution is well-known for modelling monotonic hazard rates. The commonly applied estimation technique for this class of model is the Maximum Likelihood Estimator (MLE). However, previous studies have established the inadequacy of this technique for the exponentiated class of models, such as the exponentiated-Weibull model. Thus, in this thesis, we revisited the parameter estimation for the exponentiated-Weibull model class by introducing a new Bayesian technique called Variational Bayes. We considered the case of accelerated failure time (AFT) exponentiated-Weibull regression model with covariates. The AFT model was developed using two comparative studies based on real-life Lung cancer and simulated datasets. The AFT model parameters were estimated using the MLE, Bayesian Metropolis-Hasting and Variational Bayes procedure. The data calibration results showed that the exponentiated Weibull regression adequately describes the time-toevent data. In addition, the Variational Bayesian procedure was found to be the most efficient among the three estimation techniques considered 2023-09 Thesis http://eprints.uthm.edu.my/10976/ http://eprints.uthm.edu.my/10976/1/24p%20JIBRIL%20ABUBAKAR.pdf text en public http://eprints.uthm.edu.my/10976/2/JIBRIL%20ABUBAKAR%20COPYRIGHT%20DECLARATION.pdf text en staffonly http://eprints.uthm.edu.my/10976/3/JIBRIL%20ABUBAKAR%20WATERMARK.pdf text en validuser mphil masters Universiti Tun Hussein Onn Malaysia Fakulti Sains Gunaan dan Teknologi
institution	Universiti Tun Hussein Onn Malaysia
collection	UTHM Institutional Repository
language	English English English
topic	T Technology (General)
spellingShingle	T Technology (General) Abubakar, Jibril Variational bayesian inference for exponentiated weibullright-censored survnaldata
description	The Weibull, log-logistic and log-normal distributions represent the heavy-tailed distributions that are often used in modelling time-to-event data. While the loglogistic and log-normal distributions are mainly used for modelling unimodal hazard functions, the Weibull distribution is well-known for modelling monotonic hazard rates. The commonly applied estimation technique for this class of model is the Maximum Likelihood Estimator (MLE). However, previous studies have established the inadequacy of this technique for the exponentiated class of models, such as the exponentiated-Weibull model. Thus, in this thesis, we revisited the parameter estimation for the exponentiated-Weibull model class by introducing a new Bayesian technique called Variational Bayes. We considered the case of accelerated failure time (AFT) exponentiated-Weibull regression model with covariates. The AFT model was developed using two comparative studies based on real-life Lung cancer and simulated datasets. The AFT model parameters were estimated using the MLE, Bayesian Metropolis-Hasting and Variational Bayes procedure. The data calibration results showed that the exponentiated Weibull regression adequately describes the time-toevent data. In addition, the Variational Bayesian procedure was found to be the most efficient among the three estimation techniques considered
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Abubakar, Jibril
author_facet	Abubakar, Jibril
author_sort	Abubakar, Jibril
title	Variational bayesian inference for exponentiated weibullright-censored survnaldata
title_short	Variational bayesian inference for exponentiated weibullright-censored survnaldata
title_full	Variational bayesian inference for exponentiated weibullright-censored survnaldata
title_fullStr	Variational bayesian inference for exponentiated weibullright-censored survnaldata
title_full_unstemmed	Variational bayesian inference for exponentiated weibullright-censored survnaldata
title_sort	variational bayesian inference for exponentiated weibullright-censored survnaldata
granting_institution	Universiti Tun Hussein Onn Malaysia
granting_department	Fakulti Sains Gunaan dan Teknologi
publishDate	2023
url	http://eprints.uthm.edu.my/10976/1/24p%20JIBRIL%20ABUBAKAR.pdf http://eprints.uthm.edu.my/10976/2/JIBRIL%20ABUBAKAR%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/10976/3/JIBRIL%20ABUBAKAR%20WATERMARK.pdf
_version_	1804890129372807168

Variational bayesian inference for exponentiated weibullright-censored survnaldata

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