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jeasiq-1892
Estimate the Partial Linear Model Using Wavelet and Kernel Smoothers
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This article aims to estimate the partially linear model by using two methods, which are the Wavelet and Kernel Smoothers. Simulation experiments are used to study the small sample behavior depending on different functions, sample sizes, and variances. Results explained that the wavelet smoother is the best depending on the mean average squares error criterion for all cases that used.

 

 

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Publication Date
Mon May 11 2020
Journal Name
Baghdad Science Journal
Estimating Lipoxygenase and Gamma-glutamyl Transferase Activities in Sera of Colon Cancer Patients with Partial Purification of Lipoxygenase
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            Colon cancer is an abnormal growth of cells that occurs in the large intestine. Sometimes growth remains restricted for a relatively long time before it becomes a malignant tumor and then spreads through the intestinal wall to the lymph nodes and other parts of the body. The study aims to estimate the effectiveness and partial purification of lipoxygenase (LOX) enzyme and measure gamma-glutamyle transferase (GGT) activity in serum patients of colon cancer in Baghdad. The study included (80) case male patients with colon cancer with (50) samples of apparently healthy males (control) as comparison group. The result displayed a noteworthy increase in lipoxygenase effectivene

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Publication Date
Wed Oct 28 2015
Journal Name
Journal Of Mathematics And System Science
Simulating Particle Swarm Optimization Algorithm to Estimate Likelihood Function of ARMA(1, 1) Model
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Publication Date
Wed Oct 17 2018
Journal Name
Journal Of Economics And Administrative Sciences
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 th

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Publication Date
Thu Jan 01 2015
Journal Name
International Journal Of Computer Science And Mobile Computing
Image Compression using Hierarchal Linear Polynomial Coding
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Publication Date
Sun Jun 01 2008
Journal Name
2008 Ieee International Joint Conference On Neural Networks (ieee World Congress On Computational Intelligence)
Linear block code decoder using neural network
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Publication Date
Thu Mar 01 2007
Journal Name
Journal Of Economics And Administrative Sciences
Wavelet Analysis For Sunspot Time Series
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Abstract

In this research we study the wavelet characteristics for the important time series known as Sunspot, on the aim of verifying the periodogram that other researchers had reached by the spectral transform, and noticing the variation in the period length on one side and the shifting on another.

A continuous wavelet analysis is done for this series and the periodogram in it is marked primarily. for more accuracy, the series is partitioned to its the approximate and the details components to five levels, filtering these components by using fixed threshold on one time and independent threshold on another, finding the noise series which represents the difference between

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Publication Date
Tue Mar 01 2022
Journal Name
Evergreen
Development, Validation, and Performance Evaluation of An Air-Driven Free-Piston Linear Expander Numerical Model
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Publication Date
Tue Jun 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Comparison Between Partial Least Square Regression(PLSR) and Tree Regression by Using Simulation(RT).
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This research discussed, the process of comparison between the regression model of partial least squares and tree regression, where these models included two types of statistical methods represented by the first type "parameter statistics" of the partial least squares, which is adopted when the number of variables is greater than the number of observations and also when the number of observations larger than the number of variables, the second type is the "nonparametric statistic" represented by tree regression, which is the division of data in a hierarchical way. The regression models for the two models were estimated, and then the comparison between them, where the comparison between these methods was according to a Mean Square

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Publication Date
Fri Sep 01 2017
Journal Name
International Journal Of Engineering Research And Advanced Technology
. Medical Image Compression using Hybrid Technique of Wavelet Transformation and Seed Selective Predictive Method
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Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Nonlinear Ritz Approximation for the Camassa-Holm Equation by Using the Modify Lyapunov-Schmidt method
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          In this work, the modified Lyapunov-Schmidt reduction is used to find a nonlinear Ritz approximation of Fredholm functional defined by the nonhomogeneous Camassa-Holm equation and Benjamin-Bona-Mahony. We introduced the modified Lyapunov-Schmidt reduction for nonhomogeneous problems when the dimension of the null space is equal to two.  The nonlinear Ritz approximation for the nonhomogeneous Camassa-Holm equation has been found as a function of codimension twenty-four.

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