Document Details
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Document Type |
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Thesis |
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Document Title |
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Statistical Inference for the New Dagum-X Family of Distributions: Properties and Applications الإستدلال الإحصائي حول عائلة توزيعات داجوم-اكس الجديدة:خصائصها وتطبيقاتها |
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Subject |
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Faculty of Science |
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Document Language |
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Arabic |
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Abstract |
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Various statistical distributions are still being used extensively over the previous decades for modeling data in numerous areas that include engineering, medical sciences, demography, finance and insurance. Nonetheless, in a lot of the applied areas that include lifetime analysis and finance, there is a continuous for expanded forms of these distributions. The goodness of fit of the outcome of a model depends on fitting the supposed probability distribution to the data. nevertheless, many common distributions do not fit the data well. Due to that, numerous new distributions have been constructed and examined in literature. The purpose of this thesis is to present a new family of distributions using the Dagum distribution as a generator and to study their properties such as survival function, hazard rate function, r th moment, mean, variance, quantail function, median, ordered statistics and Reni entropy. The flexibility of the new family are discussed with some real data applications. Four distributions of the Dagum family are introduced, such as: Dagum Frechet, Dagum Weibull, Dagum-Exponential and Dagum Rayleigh. The properties of these distributions such as survival function, hazard rate function, r th moment, mean, variance, quantile function, median, ordered statistics and Reniy entropy are obtained. Parameters are estimated using the maximum likelihood method, and simulations are conducted using the R program to study the behavior of the proposed distributions. Finally, the new distributions are applied to two sets of real data. The conclusion of the study indicates the flexibility of the proposed distributions in analyzing and modeling real data and the ability to use them in different applications. |
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Supervisor |
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Dr. Amani Saeed Alghamdi |
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Thesis Type |
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Master Thesis |
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Publishing Year |
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1444 AH
2023 AD |
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Co-Supervisor |
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Dr. Aisha Fayomi |
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Added Date |
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Monday, April 17, 2023 |
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Researchers
| هدى محمد الغامدي | Alghamdi, Huda Mohammed | Researcher | Master | |
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