The multiple linear regression model is an important regression model that has attracted many researchers in different fields including applied mathematics, business, medicine, and social sciences , Linear regression models involving a large number of independent variables are poorly performing due to large variation and lead to inaccurate conclusions , One of the most important problems in the regression analysis is the multicollinearity Problem, which is considered one of the most important problems that has become known to many researchers  , As well as their effects on the multiple linear regression model, In addition to multicollinearity, the problem of outliers in data is one of the difficulties in constructing the reg

يناقش هذا البحث مشكلة التعدد الخطي شبه التام في انموذج الانحدار اللاخطي ( انموذج الانحدار اللوجستي المتعدد) ، عندما يكون المتغير المعتمد متغير نوعيا يمثل ثنائي الاستجابة اما ان يساوي واحد لحدوث استجابة او صفر لعدم حدوث استجابة ، من خلال استعمال مقدرات المركبات الرئيسية التكرارية(IPCE)  التي تعتمد على الاوزان الاعتيادية والاوزان البيزية الشرطية .

اذ تم تطبيق مقدرات هذا ا

Generally, statistical methods are used in various fields of science, especially in the research field, in which Statistical analysis is carried out by adopting several techniques, according to the nature of the study and its objectives. One of these techniques is building statistical models, which is done through regression models. This technique is considered one of the most important statistical methods for studying the relationship between a dependent variable, also called (the response variable) and the other variables, called covariate variables. This research describes the estimation of the partial linear regression model, as well as the estimation of the “missing at random” values (MAR). Regarding the

Iraq suffers the continuing lack of water resources in generdwether it is surface or underearth water or rain. The study of rain has got the utmost importance in order to the rain direction in Iraq and in Mosul in particular and what it will be in future. It also shows the wet as well as the dry seasons and the possibility of expecting them and expecting their quantities in order to invest them and to keep this vital resource The research deals with predict the wet and dry rainy seasons in Mosul using (SPI) Standardized precipitation index extracted from conversion of Gamma distribution to standardized normal distribution , depending on data of monthly rain amounts for 1940-2013 . Results showed existence of 31 w

One of the most important challenges facing project management at present time is to ensure project accomplishment in spite of the specific restrictions like the specific time the financial resources specialized to do the project ; which require an accurate consideration for time and cost . the modern village project (residential building aspect) is one of the great project that ministry of agriculture is trying to do Wasit  governorate it is chosen as the work in this project is dilatory for that is being studied in term of some modern mathematical and scientific methods like critical path method (CPM)which is one of the project management and scheduling methods to know the time needed to accomplish residential building pro

      Will address this research interaction and coordination between fiscal and monetary policies and the impact of this interaction and coordination on economic stability and growth، and how the financial implications of monetary policy may stimulate action monetary policy and treatment side effects and the nature of responsiveness and bounce between procedures both two policies and their impact on the balance of overall economic and explained in the folds of searchjustifications coordination and the extent necessary in order to address the imbalances in economic activity through twinning actions of monetary and fiscal، has embodied this coordination and interaction between policies and their impact m

The method binery logistic regression and linear discrimint function of the most important statistical methods used in the classification and prediction when the data of the kind of binery (0,1) you can not use the normal regression therefore resort to binary logistic regression and linear discriminant function in the case of two group in the case of a Multicollinearity problem between the data (the data containing high correlation) It became not possible to use binary logistic regression and linear discriminant function, to solve this problem, we resort to Partial least square regression.

In this, search the comparison between binary lo

This paper presents a grey model GM(1,1) of the first rank and a variable one and is the basis of the grey system theory , This research dealt  properties of grey model and a set of methods to estimate parameters of the grey model GM(1,1)  is the least square Method (LS) , weighted least square method (WLS), total least square method (TLS) and gradient descent method  (DS). These methods were compared based on two types of standards: Mean square error (MSE), mean absolute percentage error (MAPE), and after comparison using simulation the best method was applied to real data represented by the rate of consumption of the two types of oils a Heavy fuel (HFO) and diesel fuel (D.O) and has been applied several tests to

Abstract

Characterized by the Ordinary Least Squares (OLS) on Maximum Likelihood for the greatest possible way that the exact moments are known , which means that it can be found, while the other method they are unknown, but approximations to their biases correct to 0(n^-1) can be obtained by standard methods. In our research expressions for approximations to the biases of the ML estimators (the regression coefficients and scale parameter) for linear (type 1) Extreme Value Regression Model for Largest Values are presented by using the advanced approach depends on finding the first derivative, second and third.

Abstract

   The method binery logistic regression and linear discrimint function of the most important statistical methods used in the classification and prediction when the data of the kind of binery (0,1) you can not use the normal regression therefore resort to binary logistic regression and linear discriminant function in the case of two group in the case of a Multicollinearity problem between the data (the data containing high correlation) It became not possible to use binary logistic regression and linear discriminant function, to solve this problem, we resort to Partial least square regression.

In this, search th