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discriminate analysis and logistic regression by use partial least square
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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 the comparison between binary logistic regression and linear discriminant function using error Category. Where the data has been generating a variable response (Y) binery data (0,1) containing Multicollinearity problem by the samples (50-100-150-250-400) and the variables (5-10-15). Multicollinearity problem has been processed using a method partial least square The research found that linear discriminant function It is the best in the classification of data from binary logistic regression classified as linear discriminant function the data correctly and more accurate than binary logistic regression

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Publication Date
Mon May 11 2020
Journal Name
Baghdad Science Journal
Proposing Robust LAD-Atan Penalty of Regression Model Estimation for High Dimensional Data
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         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the p

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Publication Date
Mon May 11 2020
Journal Name
Baghdad Science Journal
Proposing Robust LAD-Atan Penalty of Regression Model Estimation for High Dimensional Data
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         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the proposed LAD-Atan estimator

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Publication Date
Thu Dec 12 2013
Journal Name
Iraqi Journal Of Science
Determination of Optimum Mechanical Drilling Parameters for an Iraqi Field with Regression Model
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Publication Date
Thu Aug 14 2025
Journal Name
Journal Of The College Of Basic Education
Fuzzy Nonparametric Regression Model Estimation Based on some Smoothing Techniques With Practical Application
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In this research, we use fuzzy nonparametric methods based on some smoothing techniques, were applied to real data on the Iraqi stock market especially the data about Baghdad company for soft drinks for the year (2016) for the period (1/1/2016-31/12/2016) .A sample of (148) observations was obtained in order to construct a model of the relationship between the stock prices (Low, high, modal) and the traded value by comparing the results of the criterion (G.O.F.) for three techniques , we note that the lowest value for this criterion was for the K-Nearest Neighbor at Gaussian function .

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Publication Date
Thu Sep 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Some Methods for Estimating Mixture of Linear Regression Models with Application
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 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the others

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Publication Date
Tue Apr 04 2023
Journal Name
Journal Of Techniques
Comparison Between the Kernel Functions Used in Estimating the Fuzzy Regression Discontinuous Model
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Some experiments need to know the extent of their usefulness to continue providing them or not. This is done through the fuzzy regression discontinuous model, where the Epanechnikov Kernel and Triangular Kernel were used to estimate the model by generating data from the Monte Carlo experiment and comparing the results obtained. It was found that the. Epanechnikov Kernel has a least mean squared error.

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Publication Date
Sat Sep 20 1930
Journal Name
College Of Islamic Sciences
The causes of defeat and weakness and humiliation as described by Al - Imran: Objective study
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Praise be to Allah. Praise be to Him. We seek refuge in Him. We seek forgiveness from him. We seek forgiveness from him.
And the disadvantages of our actions, of his hands
e
It is important, if not all, to pay tribute to God
Muhammad Abdo and Rasoulou, there is no way to deprive the nation of the weakness of God alone and not to share it
 Which suffer from the Quran, and the loss of its borders, bad
The work did not work and did not improve
Do what they offer and delay the others, except by reference to this Koran and the extraction of treasures and secrets
 And news.
The Great Quran Study

Lu Imito ordered each poisoned, and achieved several targets of
YEMYA: Knowing the secrets of the Grea

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Publication Date
Tue Dec 01 2020
Journal Name
Annals Of Tropical Medicine And Public Health
Endoscopic Partial Lateral Middle Turbinectomy versus middle Turbinat Trimming in Adult patients with Concha Bullosa
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Background: Concha bullosa is an anatomical variation which defined by pneumatizaton of middle turbinate that occurred with an incidence of (5 to 25%) in the normal population.It has the potential to cause crowding and obstruction of the middle meatus and nasal cavity. There are many surgical techniques which utilized for its management. Study goal: Is to compare the formation of adhesion between endoscopic partial lateral middle turbinectomy and middle turbinate trimming in cases of concha bullosa. Patients and methods: A prospectivecomparative clinical trial was performed in the ENT department at Al-Shahid Ghazi AL Hariri Hospital in Medical City over the period from September 2016 to August 2017. Fifty nine (59) patients {24 males

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Publication Date
Wed Apr 05 2023
Journal Name
International Journal Of Interactive Mobile Technologies (ijim)
A Partial Face Encryption in Real World Experiences Based on Features Extraction from Edge Detection
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User confidentiality protection is concerning a topic in control and monitoring spaces. In image, user's faces security in concerning with compound information, abused situations, participation on global transmission media and real-world experiences are extremely significant. For minifying the counting needs for vast size of image info and for minifying the size of time needful for the image to be address computationally. consequently, partial encryption user-face is picked. This study focuses on a large technique that is designed to encrypt the user's face slightly. Primarily, dlib is utilizing for user-face detection. Susan is one of the top edge detectors with valuable localization characteristics marked edges, is used to extract

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Publication Date
Sun Mar 01 2009
Journal Name
Diyala Journal Of Human Research
Stability of the Finite Difference Methods of Fractional Partial Differential Equations Using Fourier Series Approach
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The fractional order partial differential equations (FPDEs) are generalizations of classical partial differential equations (PDEs). In this paper we examine the stability of the explicit and implicit finite difference methods to solve the initial-boundary value problem of the hyperbolic for one-sided and two sided fractional order partial differential equations (FPDEs). The stability (and convergence) result of this problem is discussed by using the Fourier series method (Von Neumanns Method).

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