مقارنة بعض طرائق التقدير اللا معلمية لنموذج الانحدار التجميعي المجزا باستعمال المحاكاة مع التطبيق == A Comparison of Some Nonparametric Estimation Methods of An Additive Quantile Regression Model Using Simulation With Application
Author name:
جنان عبد الله عنبر
Supervisor name:
دجلة ابراهيم مهدي العزاوي
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:
07T3523 - p.pdf
Abstract:
ان استعمال النماذج المعلمية يتطلب توافر معلومات كافية عن الظاهرة المدروسة مع معرفة المجتمع الذي سحبت منه العينة وان تكون معلماته معرفة لكي تكون قراءة هذه النماذج قراءة صحيحة كما تتطلب وجود بيانات من النوع الكمي الامر الذي دفع الباحثين الى البحث عن نماذج ا | Using of the parametric models requires a number of preliminary conditions that should be available to make the reading of these models right as well as the presence of quantitative data which motivated the researchers to search for models with lesser terms than the parametric models represented by nonparametric models, so too many considerations have been made for the Nonparametric Regression, in the last years. The main reason of that was the researchers’ belief that pure parametric methods for estimating the regression curve have shortage with the flexibility needed for data analysis - especially the quantitative data - . With the progress made in computers, in both hardware and software, it has become possible to develop many of Nonparametric Regression Methods including the "Quantile Methods". In spite of that, the researcher see the most of papers and articles concern univariate case, where the researchers about bivariate case still with limited. In the other hand, the researches extension to multivariate case nonexistent in Iraq - in the scope of researcher’s knowledge - , which gives an extremely importance for the aim of this study, to bring attention for alternative methods or modified methods that can be efficient ones to improve the currently methods. Thus, the most important purpose of the research, is the use of Tow - Stages method, which helps the researchers to compute Nonparametric estimators for the components of Nonparametric models to avoid the curse of dimensionality.It divideds the components to set of points called "Quantiles" , then estimates the quantile function by one of the quantile methods we explained in this research, ( Marginal Integration, Backfitting, and Tow - Stages ). The simulation has been designed for the illustrated models and it has been checked about the estimation methods performance by using the Absolute Deviation Error (ADE) criterion, then compute the Average Absolute Deviation Error (AADE). From noticing the simulation results, it was shown that the best estimator was Tow - stages estimator in case of high correlation and / or high dimensions. To achieve the purpose of this research, the study has been divided into five chapters. Chapter one, consists of an introduction, the aim of the thesis under research, and a literature survey. Chapter two covers the parametric regression quantile estimation. While Chapter three devoted for Nonparametric estimations methods. Chapter four devoted for Simulation experiments and practical experiment with real data. Finally, Chapter five comprises the conclusions and suggestions that the research has recommended.
