This research deals with a shrinking method concernes with the principal components similar to that one which used in the multiple regression “Least Absolute Shrinkage and Selection: LASS”. The goal here is to make an uncorrelated linear combinations from only a subset of explanatory variables that may have a multicollinearity problem instead taking the whole number say, (K) of them. This shrinkage will force some coefficients to equal zero, after making some restriction on them by some "tuning parameter" say, (t) which balances the bias and variance amount from side, and doesn't exceed the acceptable percent explained variance of these components. This had been shown by MSE criterion in the regression case and the percent explained v

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 Adjus

ABSTRUCT

In This Paper, some semi- parametric spatial models were estimated, these models are, the semi – parametric spatial error model (SPSEM), which suffer from the problem of spatial errors dependence, and the semi – parametric spatial auto regressive model (SPSAR). Where the method of maximum likelihood was used in estimating the parameter of spatial error          ( λ ) in the model (SPSEM), estimated  the parameter of spatial dependence ( ρ ) in the model ( SPSAR ), and using the non-parametric method in estimating the smoothing function m(x) for these two models, these non-parametric methods are; the local linear estimator (LLE) which require finding the smoo

Abstract

This study aims at identifying the impact of the application of IFRS 15 "Revenue from contracts with customers on the quality of financial reporting, through application to faculty members in the accounting departments of Iraqi universities and auditors. The problem of the study was the multiplicity of accounting rules and standards Which deals with the issues of revenue recognition , as well as the lack of consistency of most of them with the common framework of financial accounting, which results in low quality of financial reporting in the current financial statements, where the formulation of one hypothesis was the lack of relationship of significant significance The application of IFRS 15 "Recognition of rev

In order to obtain a mixed model with high significance and accurate alertness, it is necessary to search for the method that performs the task of selecting the most important variables to be included in the model, especially when the data under study suffers from the problem of multicollinearity as well as the problem of high dimensions. The research aims to compare some methods of choosing the explanatory variables and the estimation of the parameters of the regression model, which are Bayesian Ridge Regression (unbiased) and the adaptive Lasso regression model, using simulation. MSE was used to compare the methods.

This study explored the development and qualities of the response of electrochemical properties of enrofloxacin-selective electrodes using precipitation based on producing phosphotungstic, after utilizing a matrix of polyvinyl chloride (PVC) and dibutyl phthalate or dibutyl phosphate as a plasticizer. The resulting membrane sensors were an enrofloxacin-phosphotungstic electrode (sensors 1) and an ENR-DOP-PTA electrode (sensors 2). Linear responses of (ENR-DBPH-PTA) and (ENR-DOP-PTA) within the concentration ranges of 2.1×10^-6-10^-1 and 3.0×10^-6-10^-2 mol. L^-1, respectively, for both sensors were observed. Slopes of 51.61±0.24 and 39.40± 0.16 mV/decade and pH ranges equal to 2.5-8.5

Background: Moyamoya disease (MMD) is a rare cerebrovascular disease characterized by bilateral stenosis starting at the supraclinoid internal carotid artery (ICA), with the development of a collateral network of vessels. It is an established cause of stroke in the pediatric age group. Despite its increasing prevalence in various parts of the world, it remains largely underrecognized in the Middle East, particularly in Iraq. This is the first case of MMD in an Iraqi patient undergoing surgery. Case description: A 12-year-old boy presents with a 3-months history of progressive behavioural changes. MRI revealed diffuse infarcts of different ages. MRA and CT angiography revealed extensive asymmetrical steno-occlusive changes of t

In this paper, a procedure to establish the different performance measures in terms of crisp value is proposed for two classes of arrivals and multiple channel queueing models, where both arrival and service rate are fuzzy numbers. The main idea is to convert the arrival rates and service rates under fuzzy queues into crisp queues by using graded mean integration approach, which can be represented as median rule number. Hence, we apply the crisp values obtained to establish the performance measure of conventional multiple queueing models. This procedure has shown its effectiveness when incorporated with many types of membership functions in solving queuing problems. Two numerical illustrations are presented to determine the validity of the

Estimation the unknown parameters of a two-dimensional sinusoidal signal model is an important and a difficult problem , The importance of this model  in modeling Symmetric gray- scale texture image . In this paper, we propose employment Deferential Evaluation algorithm and the use of Sequential approach to estimate the unknown frequencies and amplitudes of the 2-D sinusoidal components when the signal is affected by noise. Numerical simulation are performed for different sample size, and various level of standard deviation to observe the performance of this method in estimate the parameters of 2-D sinusoidal signal model , This model was used for modeling  the Symmetric gray scale texture image and estimating by using

Background:Nocturnal Enuresis is a common problem affecting 20% of five years old children and up to 2% of adolescent and young adult. Although it is a self limiting benign condition, it has social and psychological impact on the child and his family. Many pathophysiological theories had been suggested, but none is confirmed. Hypercalciuria has been suggested to be associated with higher incidence of nocturnal enuresis. Objectives:The aim of our study to test the value of Ca/Cr ratio, on random urine sample, in diagnosing hypercalciuria in enuretic children. Type of study: Cross sectional study.Methods:Forty four enuretic children were enrolled in this study and forty five children without nocturnal enuresis were taken as control group.