{"id":27826,"date":"2019-09-26T11:07:40","date_gmt":"2019-09-26T08:07:40","guid":{"rendered":"http:\/\/ihcoedu.uobaghdad.edu.iq\/?p=27826"},"modified":"2019-09-29T09:48:12","modified_gmt":"2019-09-29T06:48:12","slug":"%d9%82%d8%b3%d9%85-%d8%a7%d9%84%d8%b1%d9%8a%d8%a7%d8%b6%d9%8a%d8%a7%d8%aa-%d9%8a%d9%86%d8%a7%d9%82%d8%b4-%d8%a7%d8%b7%d8%b1%d9%88%d8%ad%d8%a9-%d8%af%d9%83%d8%aa%d9%88%d8%b1%d8%a7%d9%87-%d8%aa","status":"publish","type":"post","link":"https:\/\/ihcoedu.uobaghdad.edu.iq\/?p=27826","title":{"rendered":"\u0642\u0633\u0645 \u0627\u0644\u0631\u064a\u0627\u0636\u064a\u0627\u062a \u064a\u0646\u0627\u0642\u0634 \u0627\u0637\u0631\u0648\u062d\u0629 \u062f\u0643\u062a\u0648\u0631\u0627\u0647 \u00a0\u062a\u0628\u062d\u062b \u0641\u064a (\u0627\u0644\u062a\u0648\u0632\u064a\u0639 \u0627\u0644\u0645\u062e\u062a\u0644\u0637 \u0627\u0644\u062c\u062f\u064a\u062f)"},"content":{"rendered":"

<\/h4>\n

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\"\"<\/p>\n

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<\/h4>\n

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<\/h4>\n

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 <\/p>\n

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\n

A New Mixture Distribution: Theory\u00a0 and\u00a0 Application<\/span><\/h3>\n

Maysaa Jalil Mohammed<\/span><\/h3>\n

Supervised by Prof. Dr. Iden Hassan Hussein<\/span><\/h3>\n

Abstract<\/span><\/h3>\n

\u00a0The objective of this thesis building\u00a0 a New Mixture distribution by incorporating three distributions which have one parameter and utilizing the survival function of Exponential, Standard Weibull and Rayleigh distributions to define “New Mixture Distribution”. The method of mixing contains three main parts: The first part includes the process of mixing the Exponential distribution and Rayleigh distribution depending on the tail in each of them. The second part mixing the Exponential distribution and Weibull distribution depending on the tail in each of them as well. Here the exponential distribution plays a big role in the mixing process in both parts.\u00a0 Finally, based on the results of the first and second parts to the blending process, the New Mixture distribution was obtained. Moreover, realizing the mathematical and statistical properties of it as the moment about the origin, incomplete moment, the moment generating function, mean , median , obtaining the characterization function and other statistical properties. Furthermore, explaining the shapes of the density function and hazard rate function for the New Mixture distribution. Using the Akaike information criterion, corrected Akaike information criterion and the Bayesian information criterion to compare the new mixture distribution with other related distributions. We illustrate the usefulness of proposed by applications of complete real data.<\/span><\/h3>\n

Later, to estimate the parameters of New Mixture distribution, used Classical estimator methods they are:(Maximum likelihood estimation method, Ordinary least square method, and the rank set sampling estimation method).<\/span><\/h3>\n

Finally, the Mean Square Error is the measured value to compare the methods above for different sizes of samples generated. Utilizing two methods of simulation technique to generate different sample sizes. We illustrate the usefulness of proposed by application of complete real data.<\/span><\/h3>\n

<\/h3>\n

<\/h4>\n","protected":false},"excerpt":{"rendered":"

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