طرائق تقدير دالة المخاطرة لتوزيع Quasi Lindely : بحث مقارن مع تطبيق عملي == Comparison of Some Methods For Estimation of Hazard Function of Distribution Quasi Lindley With Application
Author name:
احمد علوان صالح
Supervisor name:
صباح هادي عبود الجاسم
General topic:
Administration and Economics
Specific topic:
Statistics
Degree:
Master
University:
University of Baghdad - Faculty Of Administration And Economics - Department Of Statistics
Language:
Arabic
University location:
Baghdad
First pages:
07T3390 - p.pdf
Abstract:
ان البحوث المتعلقة بامراض الاطفال ومنها امراض الدم تكتسب اهمية بالغة لما تسببه هذه الامراض من زيادة في نسب الوفيات بين الاطفال مما يؤثر سلبا في نمو المجتمعات لان هذه الامراض تستهدف قاعدتها الاساسية والمتمثلة بالطفولة. من المعلوم ان التوزيعات الاحتمالية | The researches on the diseases, including children and the blood diseases is of paramount importance to what caused these diseases from an increase in mortality rates among children, which negatively affects the growth of the communities, because these diseases targeted base of basic and childhood.It is known that the probability distributions is the statistical tool that deal with times of life for patients with diseases that cause of death, and that the issue of determining the statistical distribution of the most flexible in the good compatibility with the data on life times of of people affect the accuracy of the results and specifically estimates for both parameters or a Hazard function , which provides hospital and its staff of doctors, nurses, research centers , important evidence in the medical analysis of these diseases in order to develop methods of treatment and related drugs and medical devices to other medical supplies.In this research was study the of blood leukemia disease problem in the children what caused the disease in the increase in the number of deaths for children with this disease.In this research , review the distribution of properties (Quasi Lindely - QL - ) for the proper matching the practical side data and estimate a risk function using five methods to estimate Maximum Likelihood Method , method of moments, method of L - moment Method of Percentiles Estimators and Standard Bayes Method using Squared Error Loss Function and Logarithmic Loss Function and joint prior distribution noninformative prior using (Jeffrey's formula) also used the method of Lindley Approximation to solving integrals resulting from the use Bayes way to estimate the Hazard function for this distribution.In order to find the best methods of judgment for the purpose of use in the practical side in this research were employed style simulation way (Monte Carlo) and using the Mean squared error (MSE) and the Integral. Mean square Error (IMSE) in order to compare the efficiency of the estimators to function risk was reached through implementation of simulation experiments that Bayes estimator to a Hazard function of distribution (QL) using a logarithmic function loss is the most efficient for small and medium volumes of samples while Maximum Likelihood Method and Method of Percentiles Estimators are better for large samples and at the same efficiency.Finally, in the practical side was used a sample size of data (n = 42) of the children of the deceased because of the disease leukemia blood have been employed estimator Bayes using to estimate the Hazard function loss logarithmic function to these patients. The results showed that the Hazard function of death among children in Iraq function values because of this disease are higher values than necessary health institution looks at this phenomenon and develop sophisticated prevention and treatment and to provide various medical supplies to minimize the seriousness of this disease, which leads to the depletion of human and financial resources, which negatively affects the process of progress of society as well as scientific methods should health institutions raise community awareness of the reasons this the disease for the purpose of avoiding these reasons and by employing various media, particularly newsletters that you know the reasons of the disease and treatment modalities.
