Preferred Language
Articles
/
jeasiq-725
Comparison of Partial Least Squares and Principal Components Methods by Simulation
...Show More Authors

Abstract                                                                                              

The methods of the Principal Components and Partial Least Squares can be regard very important methods  in the regression analysis, where they are used to convert a set of highly correlated variables to a set of new independent variables, known components and those components are be linear and orthogonal independent from each other , the methods are used to reduce dimensions  in regression analysis                                                                            

In this paper , we use Partial Least Squares method with  Non -linear Iterative partial least squares NIPALS(PLS1) algorithm and the principal components method with Singular Value Decomposition(SVD )algorithm  , the simulation experiments are conduct to compare between their methods  assuming that the error is normally  distributed , several combination are supposed in simulation for both sample size, number of observation, dimension, and we find that the partial least squares method is better than the Principal Components method in two case, number of observation is greater than the number of variables(n>p) and the number of variables is greater than the number of observation (p>n).                                       

Crossref
View Publication Preview PDF
Quick Preview PDF
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
...Show More Authors

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

... Show More
View Publication Preview PDF
Crossref
Publication Date
Wed Oct 17 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Two of (Turnbull) and (Generalization Turnbulls)non-parametric methods in estimating conditional survival function (applied study on breast cancer patients)
...Show More Authors

   This research includes the application of non-parametric methods in estimating the conditional survival function represented in a method (Turnbull) and (Generalization Turnbull's) using data for Interval censored of breast cancer and two types of treatment, Chemotherapy and radiation therapy and age is continuous variable, The algorithm of estimators was applied through using (MATLAB) and then the use average Mean Square Error (MSE) as amusement  to the estimates and the results showed (generalization of Turnbull's) In estimating the conditional survival function and for both treatments ,The estimated survival of the patients does not show very large differences

... Show More
View Publication Preview PDF
Crossref
Publication Date
Tue Jan 01 2019
Journal Name
International Journal Of Agricultural And Statistical Sciences,
The comparison of several methods for calculating the degree of heritability and calculating the number of genes II. Yield components
...Show More Authors

Scopus (4)
Scopus
Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Comparison Study of Electromyography Using Wavelet and Neural Network
...Show More Authors

In this paper we present a method to analyze five types with fifteen wavelet families for eighteen different EMG signals. A comparison study is also given to show performance of various families after modifying the results with back propagation Neural Network. This is actually will help the researchers with the first step of EMG analysis. Huge sets of results (more than 100 sets) are proposed and then classified to be discussed and reach the final.

View Publication Preview PDF
Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Comparison between RSA and CAST-128 with Adaptive Key for Video Frames Encryption with Highest Average Entropy
...Show More Authors

Encryption of data is translating data to another shape or symbol which enables people only with an access to the secret key or a password that can read it. The data which are encrypted are generally referred to as cipher text, while data which are unencrypted are known plain text. Entropy can be used as a measure which gives the number of bits that are needed for coding the data of an image. As the values of pixel within an image are dispensed through further gray-levels, the entropy increases. The aim of this research is to compare between CAST-128 with proposed adaptive key and RSA encryption methods for video frames to determine the more accurate method with highest entropy. The first method is achieved by applying the "CAST-128" and

... Show More
View Publication Preview PDF
Scopus (8)
Crossref (2)
Scopus Clarivate Crossref
Publication Date
Fri Apr 12 2019
Journal Name
Journal Of Economics And Administrative Sciences
Compare between simex and Quassi-likelihood methods in estimation of regression function in the presence of measurement error
...Show More Authors

       In recent years, the attention of researchers has increased of semi-parametric regression models, because it is possible to integrate the parametric and non-parametric regression models in one and then form a regression model has the potential to deal with the cruse of dimensionality in non-parametric models that occurs through the increasing of explanatory variables. Involved in the analysis and then decreasing the accuracy of the estimation. As well as the privilege of this type of model with flexibility in the application field compared to the parametric models which comply with certain conditions such as knowledge of the distribution of errors or the parametric models may

... Show More
View Publication Preview PDF
Crossref
Publication Date
Wed Jun 20 2018
Journal Name
Al-academy
Simulation and its applications in contemporary graphic design
...Show More Authors

   The simulation is the oldest theory in art, since it appeared in the Greek aesthetic thought of the philosopher Plato, as we find in many of the thinkers and philosophers over a wide period of time to reach our world today. Our fascination with art in general and design art in particular is due to the creativity and innovations of the artist through the simulation, as well as the peculiarities in this simulation, which give objects signs and signals that may have an echo that sometimes does not exist in their physical reality.

   The real representation of life and design construction, descriptions of the expression of each of them in the form of intellectual construction and the ideas of producti

... Show More
View Publication Preview PDF
Crossref
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
...Show More Authors

 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

... Show More
View Publication Preview PDF
Crossref
Publication Date
Wed Oct 17 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparison Between the Methods Estimate Nonparametric and Semiparametric Transfer Function Model in Time Series Using Simulation
...Show More Authors

Publication Date
Wed May 11 2022
Journal Name
Journal Of Economics And Administrative Sciences
Comparing Some Methods For A single Imputed A missing Observation In Estimating Nonparametric Regression Function
...Show More Authors

In this paper, we will study non parametric model when the response variable have missing data (non response) in observations it under missing mechanisms MCAR, then we suggest Kernel-Based Non-Parametric Single-Imputation instead of missing value and compare it with Nearest Neighbor Imputation by using the simulation about some difference models and with difference cases as the sample size, variance and rate of missing data.      

View Publication Preview PDF
Crossref