A Log-Beta Rayleigh Lomax Regression Model
| dc.contributor.author | Badmus, N.I. | |
| dc.contributor.author | Akinyemi, M.I. | |
| dc.contributor.author | Onyeka-Ubaka, J.N. | |
| dc.date.accessioned | 2022-09-07T12:21:12Z | |
| dc.date.available | 2022-09-07T12:21:12Z | |
| dc.date.issued | 2021 | |
| dc.description | Scholarly article | en_US |
| dc.description.abstract | For the first time, a location-scale regression model based on the logarithm of an extended Raleigh Lomax distribution which has the ability to deal and model of any survival data than classical regression model is introduced. We obtain the estimate for the model parameters using the method of maximum likelihood by considering breast cancer data. In addition, normal probability plot of the residual is used to detect the outliers and evaluate model assumptions. We use a real data set to illustrate the performance of the new model, some of its sub-models and classical models consider in the study. Also, we perform the statistics AIC, BIC and CAIC to select the most appropriate model among those regression models considered in the study. | en_US |
| dc.identifier.citation | APA 2007 | en_US |
| dc.identifier.issn | ISSN 2316-090X; DOI: http://dx.doi.org/10.16929/as/2021.2993.192 | |
| dc.identifier.uri | https://ir.unilag.edu.ng/handle/123456789/11367 | |
| dc.language.iso | en | en_US |
| dc.publisher | Afrika Statistika | en_US |
| dc.subject | Breast cancer | en_US |
| dc.subject | location-scale | en_US |
| dc.subject | logarithm | en_US |
| dc.subject | outliers | en_US |
| dc.subject | Research Subject Categories::MATHEMATICS | en_US |
| dc.title | A Log-Beta Rayleigh Lomax Regression Model | en_US |
| dc.type | Article | en_US |