A seemingly uncorrelated regression (SUR) model is a special case of multivariate models, in which the error terms in these equations are contemporaneously related. The method estimator (GLS) is efficient because it takes into account the covariance structure of errors, but it is also very sensitive to outliers. The robust SUR estimator can dealing outliers. We propose two robust methods for calculating the estimator, which are (S-Estimations, and FastSUR). We find that it significantly improved the quality of SUR model estimates. In addition, the results gave the FastSUR method superiority over the S method in dealing with outliers contained in the data set, as it has lower (MSE and RMSE) and higher (R-Squared and R-Square Adjusted) values.
This paper aims to build a modern vision for Islamic banks to ensure sustainability and growth, as well it aims to highlight the positive Iraqi steps in the Islamic banking sector. In order to build this vision, several scientific research approaches were adopted (quantitative, descriptive analytical, descriptive). As for the research community, it was for all the Iraqi private commercial banks, including Islamic banks. The research samples varied according to a diversity of the methods and the data availability. A questionnaire was constructed and conducted, measuring internal and external honesty. 50 questionnaires were distributed to Iraqi academic specialized in Islamic banking. All distributed forms were subject to a thorough analys
... Show MoreThese deposits take many forms like current acc, deposits in order to growth and serve national economy Various in varicose perspectives .
The problem of this paper its concern with un applied the mathematical models that used in profitability analysis of current acc , and deposits in view of risk, profit efficiency and financial leverage for this reason the paper discussion use the cumulate mathematical model to solve these problem, that content three variables that be used to measuring profitability by consequent replacement method by stable base and by moving base for 2007 – 2009 applied the data collect from Iraq middle east bank. &nbs
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Abstracts:
The Central Bank is the backbone of the banking system as a whole, and in order to maintain the banking system, one of the most important functions that the Central Bank performs is the function of supervising and controlling banks, with several tools and methods, and one of the most important of these tools is its creation of the function of a compliance observer, which obligated commercial banks to appoint a person in A bank that performs this function according to certain conditions and granting it some powers that would build a sound and compliant banking system. The function of the compliance observer is to follow up on the bank’s compliance with the instructions and decisions issued by
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This paper considers and proposes new estimators that depend on the sample and on prior information in the case that they either are equally or are not equally important in the model. The prior information is described as linear stochastic restrictions. We study the properties and the performances of these estimators compared to other common estimators using the mean squared error as a criterion for the goodness of fit. A numerical example and a simulation study are proposed to explain the performance of the estimators.
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Banks are considered the main basis of financial sector ,so they must be submitted to sound and strict regulatory system and so as to ensure their operations and according to instructions and regulations , in order to maintain the integrity of the banking sector and financial sector in general .One of the importance regulatory tools that are adopted by the Iraqi Central Bank to control over the banks an financial and periodic statements that are provided by the banks in accordance with planned schedules .The financial statements of the banks must reflect clearly and accurately financial situation and the result of their activities during the period in which they represent to achiveing its purposes.So it has the goal of Search is statemen
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Abstract
This research aim to overcome the problem of dimensionality by using the methods of non-linear regression, which reduces the root of the average square error (RMSE), and is called the method of projection pursuit regression (PPR), which is one of the methods for reducing dimensions that work to overcome the problem of dimensionality (curse of dimensionality), The (PPR) method is a statistical technique that deals with finding the most important projections in multi-dimensional data , and With each finding projection , the data is reduced by linear compounds overall the projection. The process repeated to produce good projections until the best projections are obtained. The main idea of the PPR is to model
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The estimation of the regular regression model requires several assumptions to be satisfied such as "linearity". One problem occurs by partitioning the regression curve into two (or more) parts and then joining them by threshold point(s). This situation is regarded as a linearity violation of regression. Therefore, the multiphase regression model is received increasing attention as an alternative approach which describes the changing of the behavior of the phenomenon through threshold point estimation. Maximum likelihood estimator "MLE" has been used in both model and threshold point estimations. However, MLE is not resistant against violations such as outliers' existence or in case of the heavy-tailed error distribution. The main goal of t
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Abstract
Due to the lack of previous statistical study of the behavior of payments, specifically health insurance, which represents the largest proportion of payments in the general insurance companies in Iraq, this study was selected and applied in the Iraqi insurance company.
In order to find the convenient model representing the health insurance payments, we initially detected two probability models by using (Easy Fit) software:
First, a single Lognormal for the whole sample and the other is a Compound Weibull for the two Sub samples (small payments and large payments), and we focused on the compoun
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The purpose behind building the linear regression model is to describe the real linear relation between any explanatory variable in the model and the dependent one, on the basis of the fact that the dependent variable is a linear function of the explanatory variables and one can use it for prediction and control. This purpose does not cometrue without getting significant, stable and reasonable estimatros for the parameters of the model, specifically regression-coefficients. The researcher found that "RUF" the criterian that he had suggested accurate and sufficient to accomplish that purpose when multicollinearity exists provided that the adequate model that satisfies the standard assumpitions of the error-term can be assigned. It
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