تقدير معلمات انحدار log-logistic باستخدام الخوارزمية الجينية مع تطبيق عملي

الموضوعات

إحصاء

روابط وملفات

التعريف والنوع

رقم الوثيقة

fb60a105-eb4f-4830-bc7a-ccb4dd8ac068

رقم العقد

0

نوع الوسائط

Crawler

نوع المحتوى

الرسائل العلمية

صيغة المصدر

رسائل ماجيستير

نوع الملف

pdf text

أسماء الملفات

2280949_1.pdf

بيانات النشر

ترجمة العنوان

Estimation of log-logistic Regression Parameters Using Genetic Algorithm with Practical Application

ألقاب المؤلفين

[{"name_ar":"حسين خليل عبيد مخيلف ","title_ar":"اعداد","title_en":"Preparation"},{"name_ar":"مشتاق كريم عبد الرحيم ","title_ar":"اشراف","title_en":"Supervision"}]

اللغة

Arabic

المصدر والدورية

اسم المصدر

تقدير معلمات انحدار log-logistic باستخدام الخوارزمية الجينية مع تطبيق عملي

المحتوى والصفحات

عدد الصفحات

0

ترجمة الملخص

In this thesis, one of the most important non-linear regression models was studied, which is the binary log-logistic model, which is used in modeling and estimating any statistical applications, and then the parameters of this model were estimated by statistical estimation methods, but when estimating its parameters, a special problem appeared to us. When the number of parameters (P+1). And if numerical methods are used to estimate its parameters, sometimes these methods do not give a better solution, because they depend directly on the primitive capabilities of the model, and accordingly we will use and employ the usual methods of estimation after improving them through the followers of one of the modern algorithms genetic algorithm) in order to suit this type A non-linear regression model for estimating its parameters. Then we compare all estimation methods. In order to choose the best methods in terms of estimation by a number of models and different sample sizes in the simulation. And based on the statistical standard (mean square error (MSE)). The comparison was made between the usual estimation methods, which included (the method of greatest possibility. And the method of chi-square minimization, the method of weighted least squares) and in the contrasts the improved estimation methods by (Genetic Algorithm), which included the method of estimating the improved maximum possible (MLE.GA) and the method of estimating the improved chi-square minimization (MCSE.GA) as well as the method of stimating the weighted least squares Enhanced (WLSE.GA). In general, it was concluded that the (WLSE) method is the best among all the usual methods for estimating the model arameters. The (MCSE.GA) method was the best among all the improved estimation methods for estimating the binary (log-logistic) model, and the reason for that is due to These two methods had the lowest (MSE) in the simulation program for all abilities compared to the rest of the methods. As for the practical side, real data was used for a sample of (90) patients with heart disease. The data was modeled and the parameters of this model were estimated and the best method was chosen, which was reached in The experimental side through the occurrence of real deaths of the injured with the estimated deaths, where it was shown the appropriateness of the binary (log-logistic) model in modeling these data and extracting the main cause of death is (smoking), as well as it was found that the (WLSE) method (MCSE.GA) They are accurate in estimating the parameters of the binary (log-logistic) model.

كلمات الباحثين

(Minimum Chi - Square Method) ,الخوارزمية الجينية(Genetic Algorithm) الانحدار الخطي , الدالة اللوجستية

إشراف وإعداد

الإشراف

مشتاق كريم عبد الرحيم

الإعداد

حسين خليل عبيد مخيلف

الاقتباسات الببليوغرافية