This paper study two stratified quantile regression models of the marginal and the conditional varieties. We estimate the quantile functions of these models by using two nonparametric methods of smoothing spline (B-spline) and kernel regression (Nadaraya-Watson). The estimates can be obtained by solve nonparametric quantile regression problem which means minimizing the quantile regression objective functions and using the approach of varying coefficient models. The main goal is discussing the comparison between the estimators of the two nonparametric methods and adopting the best one between them

Background:- Cholesterol is high in ascetic fluid due
to malignancy and other causes of exudates.
Objective:-To use cholesterol as a marker to
differentiate between exudative and transudative
ascetic fluid and to compare that with other routine
parameters.
Methods:-Twenty eight patients were included in this
study 17 females with mean age of 41.9 years, 11
males with mean age of 48.2 years. The patients were
divided in group I suspected transudate, and group II
suspected exudate according to history and clinical
examination.
Ascetic fluid samples were sent for total protein,
albumin, and cholesterol measurement blood samples
were sent for serum protein and albumin measurement.
Results:-In this

Background: The main purpose of this study is to find if there is any correlation between the level of C-reactive protein (CRP) in gingival crevicular fluid with its serum level in chronic periodontitis patients and to explore the differences between them according to the probing depth. Materials and methods: Forty seven male subjects enrolled in this study. Thirty males with chronic periodontitis considered as study group whom further subdivided according to probing depth into subgroup 1 with pocket depth ≤6mm, subgroup 2 with pocket depth >6mm. The other 17 subjects considered as controls. For all subjects, clinical examination where done for periodontal parameters plaque index (PLI), gingival index (GI), bleeding on probing (BOP),

Abstract

The multiple linear regression model of the important regression models used in the analysis for different fields of science Such as business, economics, medicine and social sciences high in data has undesirable effects on analysis results . The multicollinearity is a major problem in multiple linear regression. In its simplest state, it leads to the departure of the model parameter that is capable of its scientific properties, Also there is an important problem in regression analysis is the presence of high leverage points in the data have undesirable effects on the results of the analysis , In this research , we present some of

Study of Direct Marketing techniques and determining the scope of the suitability of each of them in the application in the Iraqi market - An analytical and explorative study for sample of views for wholesaler in Baghdad. The essential idea of the research is to go into the most important concepts which have been mentioned in the direct marketing and determining its current and most important techniques and knowing the scope of applying these techniques in Baghdad main markets (Karrada, Jamilah, shorja, Baya area, zeyouna and new Baghdad) and which of those techniques most applicable in these markets. The research took a sample of (100) wholesalers who practice the activities of selling nutritional items, auto and outs spare part

Abstract

                The research aims to identify the application of corporate governance requirements according to the international standard (ISO 26000:2010) in the National Insurance Company. Strengths and weaknesses were identified to study the current state of this requirement's application in the company under investigation. The descriptive-analytical approach was utilized through a checklist derived from ISO 26000:2010. Several personal interviews and field visits were conducted to understand the extent of application and documentation based on various statistical methods. The results revealed a level of applic

Chemical pollution is a very important issue that people suffer from and it often affects the nature of health of society and the future of the health of future generations. Consequently, it must be considered in order to discover suitable models and find descriptions to predict the performance of it in the forthcoming years. Chemical pollution data in Iraq take a great scope and manifold sources and kinds, which brands it as Big Data that need to be studied using novel statistical methods. The research object on using Proposed Nonparametric Procedure NP Method to develop an (OCMT) test procedure to estimate parameters of linear regression model with large size of data (Big Data) which comprises many indicators associated with chemi

In this work , an effective procedure of Box-Behnken based-ANN (Artificial Neural Network) and GA (Genetic Algorithm) has been utilized for finding the optimum conditions of wt.% of doping elements (Ce,Y, and Ge) doped-aluminizing-chromizing of Incoloy 800H . ANN and Box-Behnken design method have been implanted for minimizing hot corrosion rate k_p (10^-12g².cm^-4.s^-1) in Incoloy 800H at 900^oC . ANN was used for estimating the predicted values of hot corrosion rate k_p (10^-12g².cm^-4.s^-1) . The optimal wt.% of doping elements combination to obtain minimum hot corrosion rate was calculated using genetic alg