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Detecting Outliers In Multiple Linear Regression

It is well-known that the existence of outliers in the data will adversely affect the efficiency of estimation and results of the current study. In this paper four methods will be studied to detect outliers for the multiple linear regression model in two cases :  first, in real data; and secondly,  after adding the outliers to data and the attempt to detect it. The study is conducted for samples with different sizes, and uses three measures for  comparing between these methods . These three measures are : the mask, dumping and standard error of the estimate.

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Publication Date
Mon Jun 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
Use of lower squares and restricted boxes In the estimation of the first-order self-regression parameter AR (1) (simulation study)

Use of lower squares and restricted boxes
In the estimation of the first-order self-regression parameter
AR (1) (simulation study)

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Compare Estimate Methods of Parameter to Scheffʼe Mixture Model By Using Generalized Inverse and The Stepwise Regression procedure for Treatment Multicollinearity Problem

Mixture experiments are response variables based on the proportions of component for this mixture. In our research we will compare the scheffʼe model with the kronecker model for the mixture experiments, especially when the experimental area is restricted.

     Because of the experience of the mixture of high correlation problem and the problem of multicollinearity between the explanatory variables, which has an effect on the calculation of the Fisher information matrix of the regression model.

     to estimate the parameters of the mixture model, we used the (generalized inverse ) And the Stepwise Regression procedure

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Publication Date
Wed Aug 21 2019
Journal Name
Al-khwarizmi Engineering Journal
Design and Optimization of a Surface-Mounted Permanent-Magnet Linear Synchronous Motor with Maxwell ANSYS

Linear motor offers several features in many applications that require linear motion. Nevertheless, the presence of cogging force can deteriorate the thrust of a permanent magnet linear motor. Using several methodologies, a design of synchronous single sided linear iron-core motor was proposed. According to exact formulas with surface-mounted magnets and concentrated winding specification, which are relying on geometrical parameters. Two-dimensional performance analysis of the designed model and its multi-objective optimization were accomplished as a method to reduce the motor cogging force using MAXWELL ANSYS. The optimum model design results showed that the maximum force ripple was approximatrly reduced by 81.24%compared to the origina

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Publication Date
Sun May 12 2019
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Comparison of proton density MRI and T2-Weighted Fast Echo for The Detection of Cervical Spinal Cord Multiple Sclerosis Lesions

Background: The prevalence of spinal cord lesions is high in multiple sclerosis particularly in the cervical cord, and their detection can assist in both the diagnosis and follow-up of the patients. For spinal multiple sclerosis, MRI is considered the first line investigation.

Objective: To evaluate the value of sagittal 1.5 Tesla proton density-fast spin echo (PD-FSE) MRI in the detecting and increasing conspicuity of multiple sclerosis lesions in cervical cord in comparison with sagittal T2 fast spin-echo (T2-FSE) MRI.

Patients and Methods: A cross sectional study carried out from 3rd of January 2017 to 1st of January 2018 in the MRI department of

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Publication Date
Mon Jul 16 2018
Journal Name
Mathematics
Decomposition of Dynamical Signals into Jumps, Oscillatory Patterns, and Possible Outliers

In this note, we present a component-wise algorithm combining several recent ideas from signal processing for simultaneous piecewise constants trend, seasonality, outliers, and noise decomposition of dynamical time series. Our approach is entirely based on convex optimisation, and our decomposition is guaranteed to be a global optimiser. We demonstrate the efficiency of the approach via simulations results and real data analysis.

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Publication Date
Mon Jan 01 2018
Journal Name
Journal Of The College Of Languages (jcl)
Self-discovery in Paulo Coelho’s Aleph

There is no doubt that complexities and ambiguities exist in the human minds. The need to unravel and solve those mysteries and the foggy actualities of life’s existence has been one of Paulo Coelho’s (1947-present) biggest concern. In almost all his novels, Coelho shows how people should dig deep into the mysteries of life in order to find a true understanding to their existence. In doing so, a true kind of enlightenment and purification is reached and the quest for self-discovery or self-realization is attained.

    The paper tackles one of Paulo Coelho’s novels Aleph (2011) which is considered as an autobiographical reading to signify the connection between himself and God. It was a phase

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Publication Date
Thu Jun 02 2011
Journal Name
Ibn Al-haithem Journal For Pure And Applied Sciences
Publication Date
Sat Jun 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of some methods for estimating the parameters of the binary logistic regression model using the genetic algorithm with practical application

Abstract

   Suffering the human because of pressure normal life of exposure to several types of heart disease as a result of due to different factors. Therefore, and in order to find out the case of a death whether or not, are to be modeled using binary logistic regression model

    In this research used, one of the most important models of nonlinear regression models extensive use in the modeling of applications statistical, in terms of heart disease which is the binary logistic regression model. and then estimating the parameters of this model using the statistical estimation methods, another problem will be appears in estimating its parameters, as well as when the numbe

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Publication Date
Thu Dec 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Dynamic algorithm (DRBLTS) and potentially weighted (WBP) to estimate hippocampal regression parameters using a techniqueBootstrap (comparative study)

Bootstrap is one of an important re-sampling technique which has given the attention of  researches recently. The presence of outliers in the original data set may cause serious problem to the classical bootstrap when the percentage of outliers are higher than the original one. Many methods are proposed to overcome this problem such  Dynamic Robust Bootstrap for LTS (DRBLTS) and Weighted Bootstrap with Probability (WBP). This paper try to show the accuracy of parameters estimation by comparison the results of both methods. The bias , MSE and RMSE are considered. The criterion of the accuracy is based on the RMSE value since the method that provide us RMSE value smaller than other is con

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Publication Date
Sun Aug 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Proposing Robust IRWs Technique to Estimate Segmented Regression Model for the Bed load Transport of Tigris River with Change Point of Water Discharge Amount at Baghdad City

Segmented regression consists of several sections separated by different points of membership, showing the heterogeneity arising from the process of separating the segments within the research sample. This research is concerned with estimating the location of the change point between segments and estimating model parameters, and proposing a robust estimation method and compare it with some other methods that used in the segmented regression. One of the traditional methods (Muggeo method) has been used to find the maximum likelihood estimator in an iterative approach for the model and the change point as well. Moreover, a robust estimation method (IRW method) has used which depends on the use of the robust M-estimator technique in

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