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Journal of Data Science
Article . 2021 . Peer-reviewed
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https://dx.doi.org/10.60692/yk...
Other literature type . 2021
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https://dx.doi.org/10.60692/00...
Other literature type . 2021
Data sources: Datacite
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Exponentiated Weibull-Lomax Distribution: Properties and Estimation

توزيع Weibull - Lomax الأسس: الخصائص والتقدير
Authors: Amal S. Hassan; Marwa Abd-Allah;

Exponentiated Weibull-Lomax Distribution: Properties and Estimation

Abstract

Dans cet article, nous introduisons une nouvelle classe de modèle à cinq paramètres appelée Lomax de Weibull exponentié provenant de la famille générée par Weibull exponentié. La nouvelle classe contient certaines distributions existantes ainsi que de nouveaux modèles. Des expressions explicites pour ses moments, ses fonctions de distribution et de densité, ses moments de fonction de vie résiduelle sont dérivées. De plus, les entropies de Rényi et de q, les moments pondérés par probabilité et les statistiques d'ordre sont obtenus. Trois procédures d'estimation suggérées, à savoir la probabilité maximale, les moindres carrés et les moindres carrés pondérés, sont utilisées pour obtenir les estimateurs ponctuels des paramètres du modèle. Une étude de simulation est effectuée pour comparer les performances de différentes estimations en termes de biais relatifs et d'erreurs types. En outre, une application à deux ensembles de données réelles démontre l'utilité du nouveau modèle en comparaison avec certains nouveaux modèles.

En este artículo, presentamos una nueva clase de modelo de cinco parámetros llamada Exponentiated Weibull Lomax que surge de la familia generada por Exponentiated Weibull. La nueva clase contiene algunas distribuciones existentes, así como algunos modelos nuevos. Se derivan expresiones explícitas para sus momentos, funciones de distribución y densidad, momentos de función de vida residual. Además, se obtienen Rényi y q-entropías, momentos ponderados de probabilidad y estadísticas de orden. Se utilizan tres procedimientos de estimación sugeridos, a saber, la probabilidad máxima, los mínimos cuadrados y los mínimos cuadrados ponderados para obtener los estimadores puntuales de los parámetros del modelo. Se realiza un estudio de simulación para comparar el rendimiento de diferentes estimaciones en términos de sus sesgos relativos y errores estándar. Además, una aplicación a dos conjuntos de datos reales demuestra la utilidad del nuevo modelo en comparación con algunos modelos nuevos.

In this article, we introduce a new class of five-parameter model called the Exponentiated Weibull Lomax arising from the Exponentiated Weibull generated family.The new class contains some existing distributions as well as some new models.Explicit expressions for its moments, distribution and density functions, moments of residual life function are derived.Furthermore, Rényi and q-entropies, probability weighted moments, and order statistics are obtained.Three suggested procedures of estimation, namely, the maximum likelihood, least squares and weigthed least squares are used to obtain the point estimators of the model parameters.Simulation study is performed to compare the performance of different estimates in terms of their relative biases and standard errors.In addition, an application to two real data sets demonstrate the usefulness of the new model comparing with some new models.

في هذه المقالة، نقدم فئة جديدة من نموذج خمسة معلمات تسمى الأسس Weibull Lomax الناشئة عن عائلة الأسس Weibull المولدة. تحتوي الفئة الجديدة على بعض التوزيعات الحالية بالإضافة إلى بعض النماذج الجديدة. يتم اشتقاق التعبيرات الصريحة للحظات، ووظائف التوزيع والكثافة، ولحظات وظيفة الحياة المتبقية. علاوة على ذلك، يتم الحصول على Rényi و q - entropies، واللحظات المرجحة الاحتمالية، وإحصاءات الترتيب. يتم استخدام ثلاثة إجراءات مقترحة للتقدير، وهي الحد الأقصى للاحتمال، والمربعات الصغرى والمربعات الصغرى الموزونة للحصول على مقدرات النقاط لمعلمات النموذج. يتم إجراء دراسة المحاكاة لمقارنة أداء التقديرات المختلفة من حيث تحيزاتها النسبية وأخطائها القياسية. بالإضافة إلى ذلك، يوضح التطبيق على مجموعتين من البيانات الحقيقية فائدة النموذج الجديد مقارنة ببعض النماذج الجديدة.

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Keywords

Statistics and Probability, Estimator, Weibull Distribution, Lifetime Modeling, Order statistic, Artificial Intelligence, Skew Distributions and Applications in Statistics, FOS: Mathematics, Exponentiated Weibull distribution, Hidden Markov Models, Maximum Likelihood Estimation, Lomax distribution, Statistics, Applied mathematics, Algorithm, Residual, Physical Sciences, Computer Science, Weibull distribution, Model-Based Clustering with Mixture Models, Mathematics, Least-squares function approximation, Maximum likelihood

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
12
Top 10%
Average
Top 10%
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