استعمال الانتروبي مع طرائق اخرى في تقدير دالة بقاء توزيع كاما العام للسكان في العراق == Use The Entropy With Other Methods In Estimating The Survival Function of Generalized Gamma Distribution To The Population
Author name:
رغدة زياد طارق العبيدي
Supervisor name:
عمر عبد المحسن علي القيسي
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:
07T3656 - p.pdf
Abstract:
تستخدم جداول الحياة في مجالات عديدة في البحوث الديموغرافية والصحية وتمثل مؤشرا هاما للوفاة في المجتمع. ويتم احتساب جداول الحياة من بيانات الوفيات لسنة معينة للمجتمع السكاني، لذا فهو يعبر عن حالة الوفاة للمجتمع.وهناك نوعين من جداول الحياة وهي : (جداول الح | Life tables used in many fields in the demographic and health research is an important predictor of death in population. Then, calculated life tables of mortality data for a particular year the population of the community, so it reflects the rate of death of the community in somehow. There are two types of life tables, called : (Complete Life tables) and were based on the age at death on the basis of single - year age groups (0,1, 2,3,..., 81+) and were usually obtained in a manner comprehensive survey or census in order to provide detailed information on the population. The second type called (Abridged life tables) were assumed from equal death rate for ages converged with each other and are therefore based on the age at death on the five - year age groups (0 - 1, 1 - 5, 5 - 10, 10 - 15,..., 80+) which is different from its predecessor and less accuracy than is obtained in a manner sample survey. In the absence of census of our beloved Iraq, where the last census was in (1997), so be getting the calculated probability of survival through accurate (survival function) within the life tables for single - year age groups was extremely difficult and mired with disorder problems you need to mathematical treatment in accordance with the distribution of probabilistic statistical but it's distributed data showed the distribution of the Generalized Gamma : (GG) with three parameters as the best fit of the data, with this distribution in turn includes the integration of (incomplete gamma function) is implicitly making it more difficult traditional appreciation. So two major goals were arise in this thesis.The first goal of a practical application goal, using (Sprague multipliers) to convert a five - year age groups into single age. The second goal of theory using the method of Principle of Maximizing Entropy : (POME) in assessing the function of survival and to deal and overcome the turmoil and volatility demographic data collected from (Iraq Household Socio - Economic Survey : IHSES II 2012). This thesis had studied the function estimating survival data mentioned above on two parts : the first part, parametric estimation methods which is the method of Principle of Maximizing Entropy : POME, the Classical method is the Maximum Likelihood : ML. The second part, has included nonparametric method to estimate survival function by nonparametric method (Kernel Smoothing) been used as (Gaussian function). The estimation methods were compared using statistical criteria are the root mean squares error (RMSE), and the average absolute percentage error (MAPE). Among the most important conclusions, was the preference for a ML method and kernel method when a simulation to get the proportions views of the probability distribution (GG) and in a manner Inverse Transformation Method : ITM only single - year age groups sized by (n = 81) and repeat the experiment (300) replicates. As well as to reach that way entropy is the best method dealt with five - year age groups, where in the case of single - year age groups, the nonparametric kernel was best in when the practical application part. Life tables using MORTPAK program as it has been considered survival function results (UN) calculated values real and comparing the methods of the three appreciation. One of the main recommendations, the use of the (POME) to overcome the turmoil of demographic data, especially a five - year age groups and the use of Sprague data conversion from five - year age groups to transactions single - year age groups and the use of nonparametric method of kernel to assess the function of survival of the single - year age groups and entropy for five - year age groups data.
