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Comparison of Slice inverse regression with the principal components in reducing high-dimensions data by using simulation
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This research aims to study the methods of reduction of dimensions that overcome the problem curse of dimensionality when traditional methods fail to provide a good estimation of the parameters So this problem must be dealt with directly . Two methods were used to solve the problem of high dimensional data, The first method is the non-classical method Slice inverse regression ( SIR ) method and the proposed weight standard Sir (WSIR) method and principal components (PCA) which is the general method used in reducing dimensions,    (SIR ) and (PCA) is based on the work of linear combinations of a subset of the original explanatory variables, which may suffer from the problem of heterogeneity and the problem of linear multiplicity between most explanatory variables. These new combinations of linear compounds resulting from the two methods will reduce the number of explanatory variables to reach a new dimension one or more which called the effective dimension. The mean root of the error squares will be used to compare the two methods to show the preference of methods and a simulation study was conducted to compare the methods used. Simulation results showed that the proposed weight standard Sir method is the best.

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Publication Date
Fri Jun 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
"RUF procedures forgetting the best subset linear regression model"
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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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Publication Date
Wed Jan 01 2020
Journal Name
Technologies And Materials For Renewable Energy, Environment And Sustainability: Tmrees20
Change detection of the land cover for three decades using remote sensing data and geographic information system
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Publication Date
Mon Jan 02 2017
Journal Name
Journal Of Educational And Psychological Researches
Science book second grade content analysis according to the Dimensions Of Sustainable Development
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The objective of this research is to analyze the content of science textbook at the elementary level, according to the dimensions of sustainable development for the academic year (2015-2016). To achieve this goal has been to build a list with dimensions of sustainable development to be included in science textbooks in primary school, after seeing the collection of literature and research and studies, as has been reached to the list of the dimensions of the three sustainable development and social, economic and environmental in the initial image consisted of (63) the issue of sub-divided the three-dimensional, the menu and offered a group of arbitrators and specialists in curriculum and teaching methods, and thus the menu consiste

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Publication Date
Thu Oct 29 2020
Journal Name
Toxicological Research
Liver functions in combined models of the gentamicin induced nephrotoxicity and metabolic syndrome induced by high fat or fructose diets: a comparative study
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Publication Date
Sun Jan 01 2023
Journal Name
Petroleum And Coal
Analyzing of Production Data Using Combination of empirical Methods and Advanced Analytical Techniques
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Publication Date
Fri Mar 01 2019
Journal Name
Spatial Statistics
Efficient Bayesian modeling of large lattice data using spectral properties of Laplacian matrix
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Spatial data observed on a group of areal units is common in scientific applications. The usual hierarchical approach for modeling this kind of dataset is to introduce a spatial random effect with an autoregressive prior. However, the usual Markov chain Monte Carlo scheme for this hierarchical framework requires the spatial effects to be sampled from their full conditional posteriors one-by-one resulting in poor mixing. More importantly, it makes the model computationally inefficient for datasets with large number of units. In this article, we propose a Bayesian approach that uses the spectral structure of the adjacency to construct a low-rank expansion for modeling spatial dependence. We propose a pair of computationally efficient estimati

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Publication Date
Mon May 26 2025
Journal Name
Cellular And Molecular Biology
Association of cytomegalovirus and high-risk human papillomavirus with breast cancer progression
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Publication Date
Sat Jan 01 2022
Journal Name
Revista Iberoamericana De Psicologia Del Ejercicio Y El Deportethis Link Is Disabled.,
THE EFFECT OF EXERCISES WITHIN A FACTORY HIERARCHICAL STRUCTURE IN REDUCING THE DEGREE OF PAIN IN A SAMPLE OF BACK PATIENTS
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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
THe role of feeding plate in reducing some nutrirional and health problems accompaniment to cleft palate
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The present study was designed to indicate the influence of the feeding plate on the nutritional and general health problems of the isolated cleft palate infants. For this study fourteen infants were taken, their ages between one day to one week, refered from cosmetic surgery and palate center to cleft lip and palate rehabilitation center in institute of technical medical / Baghdad for feeding plate purpose . Four infants put them as normal group; all those infants were subjected during (6th) month to evaluate the body weight, feeding problem and the respiratory infection. According to tables and figures this study showed a gradual improvement in nutritional problem including (feeding problem, body weight) and health problem (such as respir

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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
SIMULATION OF OPTIMAL SPEED CONTROL FOR A DC MOTOR USING LINEAR QUADRATIC REGULATOR (LQR)
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This paper describes DC motor speed control based on optimal Linear Quadratic Regulator (LQR) technique. Controller's objective is to maintain the speed of rotation of the motor shaft with a particular step response.The controller is modeled in MATLAB environment, the simulation results show that the proposed controller gives better performance and less settling time when compared with the traditional PID controller.

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