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jeasiq-1924
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 Squares Error (MSE) and using the simulation of the experiment and by taking different sample sizes. where the results of the simulation showed that the regression of partial least squares is best when taking the following contrast variance values (0.01, 0.5, 1) and for all sample sizes, whereas tree regression is the best when it is The variance value is large (5) and for all sample sizes.

                                                                                                                      

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Publication Date
Sun Nov 01 2020
Journal Name
Iraqi Journal Of Laser
A Comparison between Er,Cr:YSGG 2780 nm Laser and Carbide Fissure Bur in Root-End resection
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Aim: The Aim of the study is to compare between Er,Cr:YSGG 2780 nm laser and carbide fissure bur in root-end resection regarding the morphological variations, temperature changes and the duration of resection process.

Settings and Design: 5 W, 25 Hz, 50% water, 80% air,25.47 J/cm2 .

Material and method: twenty-one extracted single rooted teeth endodontically were treated, twenty teeth were obturated and divided into two groups according to method of resection. Group 1 root-end resected using cross cut carbide bur while group 2 root-end resected using laser with MGG6 sapphire tip of 600 μm diameter. Temperature on external root surface and duration of resection were recor

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Publication Date
Thu Mar 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
Comparison study of Information Criteria to determine the order of Autoregressive models
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بهذا البحث نقارن معاييرالمعلومات التقليدية (AIC , SIC, HQ , FPE ) مع معيارمعلومات الانحراف المحور (MDIC) المستعملة لتحديد رتبة انموذج الانحدارالذاتي (AR) للعملية التي تولد البيانات,باستعمال المحاكاة وذلك بتوليد بيانات من عدة نماذج للأنحدارالذاتي,عندما خضوع حد الخطأ للتوزيع الطبيعي بقيم مختلفة لمعلماته

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Publication Date
Mon Mar 01 2010
Journal Name
Journal Of Economics And Administrative Sciences
Estimating the general exponential distribution parameters using the simulation method
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The main aim of this paper is to study how the different estimators of the two unknown parameters (shape and scale parameter) of a generalized exponential distribution behave for different sample sizes and for different parameter values. In particular, 

. Maximum Likelihood, Percentile and Ordinary Least Square estimators had been implemented for different sample sizes (small, medium, and large) and assumed several contrasts initial values for the two parameters. Two indicators of performance Mean Square Error and Mean Percentile Error were used and the comparisons were carried out between different methods of estimation  by using monte carlo simulation technique .. It was obse

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Publication Date
Fri Jan 01 2021
Journal Name
Annals Of Pure And Applied Mathematics
Linear Regression Model Using Bayesian Approach for Iraqi Unemployment Rate
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In this paper we used frequentist and Bayesian approaches for the linear regression model to predict future observations for unemployment rates in Iraq. Parameters are estimated using the ordinary least squares method and for the Bayesian approach using the Markov Chain Monte Carlo (MCMC) method. Calculations are done using the R program. The analysis showed that the linear regression model using the Bayesian approach is better and can be used as an alternative to the frequentist approach. Two criteria, the root mean square error (RMSE) and the median absolute deviation (MAD) were used to compare the performance of the estimates. The results obtained showed that the unemployment rates will continue to increase in the next two decade

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Publication Date
Mon Nov 11 2019
Journal Name
Spe
Modeling Rate of Penetration using Artificial Intelligent System and Multiple Regression Analysis
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Abstract<p>Over the years, the prediction of penetration rate (ROP) has played a key rule for drilling engineers due it is effect on the optimization of various parameters that related to substantial cost saving. Many researchers have continually worked to optimize penetration rate. A major issue with most published studies is that there is no simple model currently available to guarantee the ROP prediction.</p><p>The main objective of this study is to further improve ROP prediction using two predictive methods, multiple regression analysis (MRA) and artificial neural networks (ANNs). A field case in SE Iraq was conducted to predict the ROP from a large number of parame</p> ... Show More
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Publication Date
Sat Dec 31 2022
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Estimation of nonparametric regression function using shrinkage wavelet and different mother functions
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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
Fri Aug 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Using Bayesian method to estimate the parameters of Exponential Growth Model with Autocorrelation problem and different values of parameter of correlation-using simulation
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We have studied Bayesian method in this paper by using the modified exponential growth model, where this model is more using to represent the growth phenomena. We focus on three of prior functions (Informative, Natural Conjugate, and the function that depends on previous experiments) to use it in the Bayesian method. Where almost of observations for the growth phenomena are depended on one another, which in turn leads to a correlation between those observations, which calls to treat such this problem, called Autocorrelation, and to verified this has been used Bayesian method.

The goal of this study is to knowledge the effect of Autocorrelation on the estimation by using Bayesian method. F

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Publication Date
Mon Apr 09 2018
Journal Name
Al-khwarizmi Engineering Journal
Experimental Evaluation and Finite Element Simulation to Produce Square Cup by Deep Drawing Process
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Deep drawing process to produce square cup is very complex process due to a lot of process parameters which control on this process, therefore associated with it many of defects such as earing, wrinkling and fracture. Study of the effect of some process parameters to determine the values of these parameters which give the best result, the distributions for the thickness and depths of the cup were used to estimate the effect of the parameters on the cup numerically, in addition to experimental verification just to the conditions which give the best numerical predictions in order to reduce the time, efforts and costs for producing square cup with less defects experimentally is the aim of this study. The numerical analysis is used to study

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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
Robust estimation of multiple linear regression parameters in the presence of a problem of heterogeneity of variance and outliers values
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Often times, especially in practical applications, it is difficult to obtain data that is not tainted by a problem that may be related to the inconsistency of the variance of error or any other problem that impedes the use of the usual methods represented by the method of the ordinary least squares (OLS), To find the capabilities of the features of the multiple linear models, This is why many statisticians resort to the use of estimates by immune methods Especially with the presence of outliers, as well as the problem of error Variance instability, Two methods of horsepower were adopted, they are the robust weighted least square(RWLS)& the two-step robust weighted least square method(TSRWLS), and their performance was verifie

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