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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
Tue Sep 09 2014
Journal Name
Iosr Journal Of Mathematics (iosr-jm)
An Efficient Shrinkage Estimator for the Parameters of Simple Linear Regression Model
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Publication Date
Mon Apr 03 2023
Journal Name
Journal Of Electronics,computer Networking And Applied Mathematics
Comparison of Some Estimator Methods of Regression Mixed Model for the Multilinearity Problem and High – Dimensional Data
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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.

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Publication Date
Sun Feb 03 2019
Journal Name
Iraqi Journal Of Physics
Study of charge density distributions, elastic charge form factors and root-mean square radii for 4He, 12C and 16O nuclei using Woods- Saxon and harmonic-oscillator potentials
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The nuclear charge density distributions, form factors andcorresponding proton, charge, neutron, and matter root mean squareradii for stable 4He, 12C, and 16O nuclei have been calculated usingsingle-particle radial wave functions of Woods-Saxon potential andharmonic-oscillator potential for comparison. The calculations for theground charge density distributions using the Woods-Saxon potentialshow good agreement with experimental data for 4He nucleus whilethe results for 12C and 16O nuclei are better in harmonic-oscillatorpotential. The calculated elastic charge form factors in Woods-Saxonpotential are better than the results of harmonic-oscillator potential.Finally, the calculated root mean square radii usingWoods-Saxonpotentials ho

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Publication Date
Sun Feb 03 2019
Journal Name
Iraqi Journal Of Physics
Study of charge density distributions, elastic charge form factors and root-mean square radii for 4He, 12C and 16O nuclei using Woods- Saxon and harmonic-oscillator potentials
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The nuclear charge density distributions, form factors and
corresponding proton, charge, neutron, and matter root mean square
radii for stable 4He, 12C, and 16O nuclei have been calculated using
single-particle radial wave functions of Woods-Saxon potential and
harmonic-oscillator potential for comparison. The calculations for the
ground charge density distributions using the Woods-Saxon potential
show good agreement with experimental data for 4He nucleus while
the results for 12C and 16O nuclei are better in harmonic-oscillator
potential. The calculated elastic charge form factors in Woods-Saxon
potential are better than the results of harmonic-oscillator potential.
Finally, the calculated root mean square

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Publication Date
Fri Oct 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Renewable energy between limited use and treatment of the electricity crisis in Iraq
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The electric energy is one of the most important renewable energies used in the world as it is the main source for sustainable development and economic development through its use in (production, transport and distribution), and in Iraq, the electric power sector has suffered from many problems and obstacles, as providing electric current is one of the most prominent difficulties and challenges That successive governments and residents have faced since the early nineties of the last century and are still ongoing, and that Iraq has all the climatic conditions for developing the work of the electricity system from renewable energies such as solar and hydroelectric energy, as well as gas fields that have become a Basic pillar of pow

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
Real-Time Cloth Simulation on Virtual Human Character Using Enhanced Position Based Dynamic Framework Technique
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     Cloth simulation and animation has been the topic of research since the mid-80's in the field of computer graphics. Enforcing incompressible is very important in real time simulation. Although, there are great achievements in this regard, it still suffers from unnecessary time consumption in certain steps that is common in real time applications.   This research develops a real-time cloth simulator for a virtual human character (VHC) with wearable clothing. This research achieves success in cloth simulation on the VHC through enhancing the position-based dynamics (PBD) framework by computing a series of positional constraints which implement constant densities. Also, the self-collision and collision wit

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
A Comparison Between Some Estimator Methods of Linear Regression Model With Auto-Correlated Errors With Application Data for the Wheat in Iraq
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This research a study model of linear regression problem of autocorrelation of random error is spread when a normal distribution as used in linear regression analysis for relationship between variables and through this relationship can predict the value of a variable with the values of other variables, and was comparing methods (method of least squares, method of the average un-weighted, Thiel method and Laplace method) using the mean square error (MSE) boxes and simulation and the study included fore sizes of samples (15, 30, 60, 100). The results showed that the least-squares method is best, applying the fore methods of buckwheat production data and the cultivated area of the provinces of Iraq for years (2010), (2011), (2012),

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Publication Date
Tue Oct 23 2018
Journal Name
Journal Of Economics And Administrative Sciences
Compare some wavelet estimators for parameters in the linear regression model with errors follows ARFIMA model.
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The aim of this research is to estimate the parameters of the linear regression model with errors following ARFIMA model by using wavelet method depending on maximum likelihood and approaching general least square as well as ordinary least square. We use the estimators in practical application on real data, which were the monthly data of Inflation and Dollar exchange rate obtained from the (CSO) Central Statistical organization for the period from 1/2005 to 12/2015. The results proved that (WML) was the most reliable and efficient from the other estimators, also the results provide that the changing of fractional difference parameter (d) doesn’t effect on the results.

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Publication Date
Fri Mar 31 2017
Journal Name
Al-khwarizmi Engineering Journal
Big-data Management using Map Reduce on Cloud: Case study, EEG Images' Data
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Database is characterized as an arrangement of data that is sorted out and disseminated in a way that allows the client to get to the data being put away in a simple and more helpful way. However, in the era of big-data the traditional methods of data analytics may not be able to manage and process the large amount of data. In order to develop an efficient way of handling big-data, this work studies the use of Map-Reduce technique to handle big-data distributed on the cloud. This approach was evaluated using Hadoop server and applied on EEG Big-data as a case study. The proposed approach showed clear enhancement for managing and processing the EEG Big-data with average of 50% reduction on response time. The obtained results provide EEG r

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Publication Date
Wed Dec 01 2010
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
إستخدام التحليل الهرمي (AHP) في المفاضلة لإختيار المجهزين: دراسة حالة في الشركة العامة للمسح الجيولوجي والتعدين
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Analytical Hierarchy Process (AHP) belongs to the family of Multiple Criteria Decision Making (MCDM)  and has, recently, received a wide popularity in decision making regarding supplier selection.  The objective of this study is to apply the methodology of AHP on selecting suppliers to supply materials for the  Geological Survey and Mining  Company (GSMC).  Criteria for rating the suppliers and pairwise comparisons were identified by the members of the Tenders Analysis Committee (TAC). In order to judge the internal validity of the AHP, it was applied manually on a sample of fourteen tenders that were analyzed  and executed between 2004-2007, then an interactive computerized  package was developed 

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