Abstract                                                                                              

The methods of the Principal Components and Partial Least Squares can be regard very important methods  in the regression analysis, whe

يعد أنموذج الانحدار اللوجستي من نماذج الانحدار المهمة، حيث يلقى اهتماماً واضحاً في معظم الدراسات التي تأخذ طابعاً اكثر تقدماً في عملية التحليل الاحصائي. أن طرائق التقدير الاعتيادية تفشل في التعامل مع البيانات التي تتضمن وجود القيم الشاذة حيث أن لها تأثير غير مرغوب على النتائج. سنستعرض في هذا البحث طرائق لتقدير معلمات انموذج الانحدار اللوجستي وهذه الطرائق هي: طريقة مقدر لابلاس (Laplace estimator) (LP-) وطريقة مقدر هوب

Abstract

The research examined with the importance banking merger to address the situation of Troubled banks in Iraq, Through The use of Logistic Regression Model. . The study attempted to present a conceptual aspect of banking merger and logistic regression, as well as the applied aspect which includes a sample consisting of six private Iraqi banks, and the hypothesis of the study is that the promotion of mergers among banks has positive impacts on improving the efficiency of performance of troubled banks, which contributes to the increase of banking services, raise of their financial indicators and the high liquidity and profits of the new banking entity as it is a way to overcome the prevailing banking crises.

Maulticollinearity is a problem that always occurs when two or more predictor variables are correlated with each other. consist of the breach of one basic assumptions of the ordinary least squares method with biased estimates results, There are several methods which are proposed to handle this problem including the  method To address a problem  and  method To address a problem , In this research a comparisons are employed between the biased   method and unbiased   method with Bayesian   using Gamma distribution  method  addition to Ordinary Least Square metho

In this study, we focused on the random coefficient estimation of the general regression and Swamy models of panel data. By using this type of data, the data give a better chance of obtaining a better method and better indicators. Entropy's methods have been used to estimate random coefficients for the general regression and Swamy of the panel data which were presented in two ways: the first represents the maximum dual Entropy and the second is general maximum Entropy in which a comparison between them have been done by using simulation to choose the optimal methods.

The results have been compared by using mean squares error and mean absolute percentage error to different cases in term of correlation valu

 ABSTRICT:

  This study is concerned with the estimation of constant  and time-varying parameters in non-linear ordinary differential equations, which do not have analytical solutions. The estimation is done in a multi-stage method where constant and time-varying parameters are estimated in a straight sequential way from several stages. In the first stage, the model of the differential equations is converted to a regression model that includes the state variables with their derivatives and then the estimation of the state variables and their derivatives in a penalized splines method and compensating the estimations in the regression model. In the second stage, the pseudo- least squares method was used to es

    This article aims to explore the importance of estimating the a semiparametric regression function ,where we suggest a new estimator beside the other combined estimators and then we make a comparison among them by using simulation technique . Through the simulation results we find  that the suggest estimator is the best with the first and second models ,wherealse for the third model we find Burman and Chaudhuri (B&C) is best.

The logistic regression model regarded as the important regression Models ,where of the most interesting subjects in recent studies due to taking character more advanced in the process of statistical analysis .                                                

The ordinary estimating methods is failed in dealing with data that consist of the presence of outlier values and hence on the absence of such that have undesirable effect on the result.    &nbs

Abstract

Multivariate GARCH Models take several forms , the most important DCC dynamic conditional correlation, and CCC constant conditional correlation , The Purpose of this research is the Comparison for both Models.Using three  financial time series which is a series of daily Iraqi dinar exchange rate indollar, Global daily Oil price in dollar and Global daily gold price in dollarfor the period from 01/01/2014 till 01/01/2016, Where it has been transferred to the three time series returns to get the Stationarity, some tests were conducted including Ljung-Box , JarqueBera  , Multivariate ARCH to Returns Series and Residuals Series for both models In Comparison

بهذا البحث نقارن معاييرالمعلومات التقليدية (AIC , SIC, HQ , FPE ) مع معيارمعلومات الانحراف المحور (MDIC) المستعملة لتحديد رتبة انموذج الانحدارالذاتي (AR) للعملية التي تولد البيانات,باستعمال المحاكاة وذلك بتوليد بيانات من عدة نماذج للأنحدارالذاتي,عندما خضوع حد الخطأ للتوزيع الطبيعي بقيم مختلفة لمعلماته