Variational Bayesian inference for exponentiated Weibull right censored survival data
The exponential, Weibull, log-logistic and lognormal distributions represent the class of light and heavy-tailed distributions that are often used in modelling time-to-event data. The exponential distribution is often applied if the hazard is constant, while the log-logistic and lognormal distribut...
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IAPress
2023
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| Online Access: | http://eprints.uthm.edu.my/10607/1/J16598_c0a325c6c23e6e60f2862fca55685b2b.pdf http://eprints.uthm.edu.my/10607/ https://doi.org/10.19139/soic-2310-5070-1295 |
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| author | Jibril Abubakar, Jibril Abubakar Mohd Asrul Affendi Abdullah, Mohd Asrul Affendi Abdullah Oyebayo Ridwan Olaniran, Oyebayo Ridwan Olaniran |
| author_facet | Jibril Abubakar, Jibril Abubakar Mohd Asrul Affendi Abdullah, Mohd Asrul Affendi Abdullah Oyebayo Ridwan Olaniran, Oyebayo Ridwan Olaniran |
| author_sort | Jibril Abubakar, Jibril Abubakar |
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| content_provider | Universiti Tun Hussein Onn Malaysia |
| content_source | UTHM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | The exponential, Weibull, log-logistic and lognormal distributions represent the class of light and heavy-tailed
distributions that are often used in modelling time-to-event data. The exponential distribution is often applied if the hazard is constant, while the log-logistic and lognormal distributions are mainly used for modelling unimodal hazard functions. The Weibull distribution is on the other hand well-known for modelling monotonic hazard rates. Recently, in practice, survival data often exhibit both monotone and non-monotone hazards. This gap has necessitated the introduction of Exponentiated Weibull Distribution (EWD) that can accommodate both monotonic and non-monotonic hazard functions. It also has the strength of adapting unimodal functions with bathtub shape. Estimating the parameter of EWD distribution poses another problem as the flexibility calls for the introduction of an additional parameter. Parameter estimation using the maximum likelihood approach has no closed-form solution, and thus, approximation techniques such as Newton-Raphson is often
used. Therefore, in this paper, we introduce another estimation technique called Variational Bayesian (VB) approach. We considered the case of the accelerated failure time (AFT) regression model with covariates. The AFT model was developed using two comparative studies based on real-life and simulated data sets. The results from the experiments reveal that the Variational Bayesian (VB) approach is better than the competing Metropolis-Hasting Algorithm and the reference maximum likelihood estimates. |
| format | Article |
| id | my.uthm.eprints-10607 |
| institution | Universiti Tun Hussein Onn Malaysia |
| language | en |
| publishDate | 2023 |
| publisher | IAPress |
| record_format | eprints |
| spelling | my.uthm.eprints-106072024-01-15T07:30:26Z http://eprints.uthm.edu.my/10607/ Variational Bayesian inference for exponentiated Weibull right censored survival data Jibril Abubakar, Jibril Abubakar Mohd Asrul Affendi Abdullah, Mohd Asrul Affendi Abdullah Oyebayo Ridwan Olaniran, Oyebayo Ridwan Olaniran T Technology (General) The exponential, Weibull, log-logistic and lognormal distributions represent the class of light and heavy-tailed distributions that are often used in modelling time-to-event data. The exponential distribution is often applied if the hazard is constant, while the log-logistic and lognormal distributions are mainly used for modelling unimodal hazard functions. The Weibull distribution is on the other hand well-known for modelling monotonic hazard rates. Recently, in practice, survival data often exhibit both monotone and non-monotone hazards. This gap has necessitated the introduction of Exponentiated Weibull Distribution (EWD) that can accommodate both monotonic and non-monotonic hazard functions. It also has the strength of adapting unimodal functions with bathtub shape. Estimating the parameter of EWD distribution poses another problem as the flexibility calls for the introduction of an additional parameter. Parameter estimation using the maximum likelihood approach has no closed-form solution, and thus, approximation techniques such as Newton-Raphson is often used. Therefore, in this paper, we introduce another estimation technique called Variational Bayesian (VB) approach. We considered the case of the accelerated failure time (AFT) regression model with covariates. The AFT model was developed using two comparative studies based on real-life and simulated data sets. The results from the experiments reveal that the Variational Bayesian (VB) approach is better than the competing Metropolis-Hasting Algorithm and the reference maximum likelihood estimates. IAPress 2023 Article PeerReviewed text en http://eprints.uthm.edu.my/10607/1/J16598_c0a325c6c23e6e60f2862fca55685b2b.pdf Jibril Abubakar, Jibril Abubakar and Mohd Asrul Affendi Abdullah, Mohd Asrul Affendi Abdullah and Oyebayo Ridwan Olaniran, Oyebayo Ridwan Olaniran (2023) Variational Bayesian inference for exponentiated Weibull right censored survival data. STATISTICS, OPTIMIZATION AND INFORMATION COMPUTING, 11. pp. 1027-1040. https://doi.org/10.19139/soic-2310-5070-1295 |
| spellingShingle | T Technology (General) Jibril Abubakar, Jibril Abubakar Mohd Asrul Affendi Abdullah, Mohd Asrul Affendi Abdullah Oyebayo Ridwan Olaniran, Oyebayo Ridwan Olaniran Variational Bayesian inference for exponentiated Weibull right censored survival data |
| title | Variational Bayesian inference for exponentiated Weibull right censored survival data |
| title_full | Variational Bayesian inference for exponentiated Weibull right censored survival data |
| title_fullStr | Variational Bayesian inference for exponentiated Weibull right censored survival data |
| title_full_unstemmed | Variational Bayesian inference for exponentiated Weibull right censored survival data |
| title_short | Variational Bayesian inference for exponentiated Weibull right censored survival data |
| title_sort | variational bayesian inference for exponentiated weibull right censored survival data |
| topic | T Technology (General) |
| url | http://eprints.uthm.edu.my/10607/1/J16598_c0a325c6c23e6e60f2862fca55685b2b.pdf http://eprints.uthm.edu.my/10607/ https://doi.org/10.19139/soic-2310-5070-1295 |
| url_provider | http://eprints.uthm.edu.my/ |