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On Modeling the Earthquake Insurance Data via a New Member of the T-X Family
المؤلفون المشاركون
Ahmad, Zubair
Mahmoudi, Eisa
Kharazmi, Omid
المصدر
Computational Intelligence and Neuroscience
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-20، 20ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-09-19
دولة النشر
مصر
عدد الصفحات
20
التخصصات الرئيسية
الملخص EN
Heavy-tailed distributions play an important role in modeling data in actuarial and financial sciences.
In this article, a new method is suggested to define new distributions suitable for modeling data with a heavy right tail.
The proposed method may be named as the Z-family of distributions.
For illustrative purposes, a special submodel of the proposed family, called the Z-Weibull distribution, is considered in detail to model data with a heavy right tail.
The method of maximum likelihood estimation is adopted to estimate the model parameters.
A brief Monte Carlo simulation study for evaluating the maximum likelihood estimators is done.
Furthermore, some actuarial measures such as value at risk and tail value at risk are calculated.
A simulation study based on these actuarial measures is also done.
An application of the Z-Weibull model to the earthquake insurance data is presented.
Based on the analyses, we observed that the proposed distribution can be used quite effectively in modeling heavy-tailed data in insurance sciences and other related fields.
Finally, Bayesian analysis and performance of Gibbs sampling for the earthquake data have also been carried out.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Ahmad, Zubair& Mahmoudi, Eisa& Kharazmi, Omid. 2020. On Modeling the Earthquake Insurance Data via a New Member of the T-X Family. Computational Intelligence and Neuroscience،Vol. 2020, no. 2020, pp.1-20.
https://search.emarefa.net/detail/BIM-1138816
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Ahmad, Zubair…[et al.]. On Modeling the Earthquake Insurance Data via a New Member of the T-X Family. Computational Intelligence and Neuroscience No. 2020 (2020), pp.1-20.
https://search.emarefa.net/detail/BIM-1138816
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Ahmad, Zubair& Mahmoudi, Eisa& Kharazmi, Omid. On Modeling the Earthquake Insurance Data via a New Member of the T-X Family. Computational Intelligence and Neuroscience. 2020. Vol. 2020, no. 2020, pp.1-20.
https://search.emarefa.net/detail/BIM-1138816
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1138816
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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