On the Extension of the Burr XII Distribution: Applications and Regression
In this paper, we introduce a new four-parameter mixture distribution called the Harmonic Mixture Burr XII distribution. The proposed model can be used to model data which exhibit bimodal shapes or are heavy-tailed. Specific properties like non-central and incomplete moments, quantile function, ent...
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| Format: | Article |
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The Scientific Association for Studies and Applied Research
2023-04-01
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| Series: | Computational Journal of Mathematical and Statistical Sciences |
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| Online Access: | https://cjmss.journals.ekb.eg/issue_39255_39256.html |
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| author | SELASI KWAKU OCLOO LEWIS BREW SULEMAN NASIRU BENJAMIN ODOI |
| author_facet | SELASI KWAKU OCLOO LEWIS BREW SULEMAN NASIRU BENJAMIN ODOI |
| author_sort | SELASI KWAKU OCLOO |
| collection | DOAJ |
| description | In this paper, we introduce a new four-parameter mixture distribution called the Harmonic Mixture Burr XII distribution. The proposed model can be used to model data which exhibit bimodal shapes or are heavy-tailed. Specific properties like non-central and incomplete moments, quantile function, entropy, mean and median deviation, mean residual life, moment generating function, and stress-strength reliability are derived. Maximum likelihood estimation, ordinary least squares estimation, weighted least squares estimation, Cram'{e}r-von Mises estimation, and Anderson-Darling estimation methods were used to estimate the parameters of the distribution. Simulation studies was performed to assess the estimators and the maximum likelihood estimation was adjudged the best estimator. Using three sets of lifetime data, the empirical importance of the new distribution was determined. When compared to nine (9) extensions of the Burr XII distribution, it was clear that the proposed distribution fit the data better. Using the proposed model, a log-linear regression model called the log-harmonic mixture Burr XII is proposed.
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| format | Article |
| id | doaj-art-bc9cefa1b2f94de88f84ee4546f57bbb |
| institution | OA Journals |
| issn | 2974-3435 2974-3443 |
| language | English |
| publishDate | 2023-04-01 |
| publisher | The Scientific Association for Studies and Applied Research |
| record_format | Article |
| series | Computational Journal of Mathematical and Statistical Sciences |
| spelling | doaj-art-bc9cefa1b2f94de88f84ee4546f57bbb2025-08-20T02:10:49ZengThe Scientific Association for Studies and Applied ResearchComputational Journal of Mathematical and Statistical Sciences2974-34352974-34432023-04-012113010.21608/CJMSS.2023.181739.1000On the Extension of the Burr XII Distribution: Applications and RegressionSELASI KWAKU OCLOO0LEWIS BREW 1SULEMAN NASIRU2BENJAMIN ODOI 3University of Mines and Technology, Tarkwa.University of Mines and Technology, Tarkwa.Department of Statistics, C.K. Tedam University of Technology and Applied Sciences, GhanaUniversity of Mines and Technology, Tarkwa.In this paper, we introduce a new four-parameter mixture distribution called the Harmonic Mixture Burr XII distribution. The proposed model can be used to model data which exhibit bimodal shapes or are heavy-tailed. Specific properties like non-central and incomplete moments, quantile function, entropy, mean and median deviation, mean residual life, moment generating function, and stress-strength reliability are derived. Maximum likelihood estimation, ordinary least squares estimation, weighted least squares estimation, Cram'{e}r-von Mises estimation, and Anderson-Darling estimation methods were used to estimate the parameters of the distribution. Simulation studies was performed to assess the estimators and the maximum likelihood estimation was adjudged the best estimator. Using three sets of lifetime data, the empirical importance of the new distribution was determined. When compared to nine (9) extensions of the Burr XII distribution, it was clear that the proposed distribution fit the data better. Using the proposed model, a log-linear regression model called the log-harmonic mixture Burr XII is proposed. https://cjmss.journals.ekb.eg/issue_39255_39256.htmlburr xii distributionheavy-tailed distributionsimulationapplicationsregression |
| spellingShingle | SELASI KWAKU OCLOO LEWIS BREW SULEMAN NASIRU BENJAMIN ODOI On the Extension of the Burr XII Distribution: Applications and Regression Computational Journal of Mathematical and Statistical Sciences burr xii distribution heavy-tailed distribution simulation applications regression |
| title | On the Extension of the Burr XII Distribution: Applications and Regression |
| title_full | On the Extension of the Burr XII Distribution: Applications and Regression |
| title_fullStr | On the Extension of the Burr XII Distribution: Applications and Regression |
| title_full_unstemmed | On the Extension of the Burr XII Distribution: Applications and Regression |
| title_short | On the Extension of the Burr XII Distribution: Applications and Regression |
| title_sort | on the extension of the burr xii distribution applications and regression |
| topic | burr xii distribution heavy-tailed distribution simulation applications regression |
| url | https://cjmss.journals.ekb.eg/issue_39255_39256.html |
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