Please use this identifier to cite or link to this item: http://148.72.244.84/xmlui/handle/xmlui/14906
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dc.contributor.authorAlhaji Modu Isa, Alaa Abdulrahman Khalaf-
dc.contributor.authorSule Omeiza Bashiru-
dc.date.accessioned2024-10-03T19:44:42Z-
dc.date.available2024-10-03T19:44:42Z-
dc.date.issued2024-09-30-
dc.identifier.citationhttps://ijas.uodiyala.edu.iq/index.php/IJAS/article/view/78/12en_US
dc.identifier.issn3006-5828-
dc.identifier.urihttp://148.72.244.84:8080/xmlui/handle/xmlui/14906-
dc.description.abstracthis paper introduces a new trigonometric distribution, named the Cosine Lomax (CLM) distribution. This distribution is a combination of the Lomax distribution and the Cosine-G family of distributions. Among the many mathematical moments, moment-generating function, incomplete moments, and the quantile function. We try to determine the model parameters using the maximum likelihood estimation method. Simulation studies evaluate the effectiveness of maximum likelihood estimators using bias and root mean square error. We applied the CLM distribution to two real-world datasets and tested for consistency using the Akaike information criterion, the consistent AIC, the Hannan-Quinn information criterion, the Bayesian information criterion, the Kolmogorov-Smirnov p-value, Cramer Von-Mises, and Andersen-Darling. The CLM model fared better when compared to the following distributions: Lomax, Inverse Lomax, Inverse Weibull, Burr Type X, Rayleigh, and Exponential, as well as measures of data set fit.en_US
dc.language.isoenen_US
dc.publisherUniversity of Diyala – College of Education for Pure Sciencesen_US
dc.subjectCosine –G, family Lomax , Distribution, Moment, Incomplete Moment, MLEen_US
dc.titleSome Properties of the Cosine Lomax Distribution with Applicationsen_US
dc.typeArticleen_US
Appears in Collections:المجلة العراقية للعلوم التطبيقية / Iraqi Journal for Applied Science

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