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bsj-6476
K-Nearest Neighbor Method with Principal Component Analysis for Functional Nonparametric Regression
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This paper proposed a new  method to study functional non-parametric regression data analysis with conditional expectation in the case that the covariates  are functional and the Principal Component Analysis was utilized to de-correlate the multivariate response variables. It  utilized the formula of the Nadaraya Watson estimator (K-Nearest Neighbour (KNN)) for prediction with different types of the semi-metrics, (which are based on Second Derivative and Functional Principal Component Analysis (FPCA))  for measureing the closeness between curves.  Root Mean Square Errors is used for the  implementation of this model which is then compared to the independent response method. R program is used for analysing data. Then, when  the covariates  are functional and the Principal Component Analysis was utilized to de-correlate the multivariate response variables model, results are more preferable than the independent response method. The models are demonstrated by both a simulation data and real data.

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Publication Date
Fri Sep 06 2024
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Some Wavelet Transformations to Estimate Nonparametric Regression Function
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The purpose of this article is to improve and minimize noise from the signal by studying wavelet transforms and showing how to use the most effective ones for processing and analysis. As both the Discrete Wavelet Transformation method was used, we will outline some transformation techniques along with the methodology for applying them to remove noise from the signal. Proceeds based on the threshold value and the threshold functions Lifting Transformation, Wavelet Transformation, and Packet Discrete Wavelet Transformation. Using AMSE, A comparison was made between them , and the best was selected. When the aforementioned techniques were applied to actual data that was represented by each of the prices, it became evident that the lift

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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
A comparison among Different Methods for Estimating Regression Parameters with Autocorrelation Problem under Exponentially Distributed Error
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Multiple linear regressions are concerned with studying and analyzing the relationship between the dependent variable and a set of explanatory variables. From this relationship the values of variables are predicted. In this paper the multiple linear regression model and three covariates were studied in the presence of the problem of auto-correlation of errors when the random error distributed the distribution of exponential. Three methods were compared (general least squares, M robust, and Laplace robust method). We have employed the simulation studies and calculated the statistical standard mean squares error with sample sizes (15, 30, 60, 100). Further we applied the best method on the real experiment data representing the varieties of

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Publication Date
Mon Mar 03 2025
Journal Name
Internationaljournalof Economicsandfinancestudies
CROSS-SECTIONAL REGRESSION WITH PROXIES: A SEMI-PARAMETRIC METHOD
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This study investigates asset returns within the Iraq Stock Exchange by employing both the Fama-MacBeth regression model and the Fama-French three-factor model. The research involves the estimation of cross-sectional regressions wherein model parameters are subject to temporal variation, and the independent variables function as proxies. The dataset comprises information from the first quarter of 2010 to the first quarter of 2024, encompassing 22 publicly listed companies across six industrial sectors. The study explores methodological advancements through the application of the Single Index Model (SIM) and Kernel Weighted Regression (KWR) in both time series and cross-sectional analyses. The SIM outperformed the K

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Scopus
Publication Date
Thu Dec 28 2017
Journal Name
Al-khwarizmi Engineering Journal
An Autocorrelative Approach for EMG Time-Frequency Analysis
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As they are the smallest functional parts of the muscle, motor units (MUs) are considered as the basic building blocks of the neuromuscular system. Monitoring MU recruitment, de-recruitment, and firing rate (by either invasive or surface techniques) leads to the understanding of motor control strategies and of their pathological alterations. EMG signal decomposition is the process of identification and classification of individual motor unit action potentials (MUAPs) in the interference pattern detected with either intramuscular or surface electrodes. Signal processing techniques were used in EMG signal decomposition to understand fundamental and physiological issues. Many techniques have been developed to decompose intramuscularly detec

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Publication Date
Wed Nov 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Estimate missing value by use analyses of covariance method for split block-design
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The research aims to estimate missing values using covariance analysis method Coons way to the variable response or dependent variable that represents the main character studied in a type of multi-factor designs experiments called split block-design (SBED) so as to increase the accuracy of the analysis results and the accuracy of statistical tests based on this type of designs. as it was noted in the theoretical aspect to the design of dissident sectors and statistical analysis have to analyze the variation in the experience of experiment )SBED) and the use of covariance way coons analysis according to two methods to estimate the missing value, either in the practical side of it has been implemented field experiment wheat crop in

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Publication Date
Thu Dec 31 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Application of data content analysis (DEA) technology to evaluate performance efficiency: applied research in the General Tax Authority
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The aim of the research is to use the data content analysis technique (DEA) in evaluating the efficiency of the performance of the eight branches of the General Tax Authority, located in Baghdad, represented by Karrada, Karkh parties, Karkh Center, Dora, Bayaa, Kadhimiya, New Baghdad, Rusafa according to the determination of the inputs represented by the number of non-accountable taxpayers and according to the categories professions and commercial business, deduction, transfer of property ownership, real estate and tenders, In addition to determining the outputs according to the checklist that contains nine dimensions to assess the efficiency of the performance of the investigated branches by investing their available resources T

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Publication Date
Wed Jan 04 2023
Journal Name
College Of Islamic Sciences
Predicting the financial distress of companies using logistic regression and its impact on earnings per share in companies listed on the Iraqi Stock Exchange: Predicting the financial distress of companies using logistic regression and its impact on earnings per share in companies listed on the Iraqi Stock Exchange
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Abstract

The prevention of bankruptcy not only prolongs the economic life of the company and increases its financial performance, but also helps to improve the general economic well-being of the country. Therefore, forecasting the financial shortfall can affect various factors and affect different aspects of the company, including dividends. In this regard, this study examines the prediction of the financial deficit of companies that use the logistic regression method and its impact on the earnings per share of companies listed on the Iraqi Stock Exchange. The time period of the research is from 2015 to 2020, where 33 companies that were accepted in the Iraqi Stock Exchange were selected as a sample, and the res

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Publication Date
Thu Apr 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Comparison Between Tree regression (TR), and Negative binomial regression (NBR) by Using Simulation.
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            In this paper, the process of comparison between the tree regression model and the negative binomial regression. As these models included two types of statistical methods represented by the first type "non parameter statistic" which is the tree regression that aims to divide the data set into subgroups, and the second type is the "parameter statistic" of negative binomial regression, which is usually used when dealing with medical data, especially when dealing with large sample sizes. Comparison of these methods according to the average mean squares error (MSE) and using the simulation of the experiment and taking different sample

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Crossref
Publication Date
Fri Dec 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
A Comparison between Methods of Laplace Estimators and the Robust Huber for Estimate parameters logistic regression model
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The logistic regression model regarded as the important regression Models ,where of the most interesting subjects in recent studies due to taking character more advanced in the process of statistical analysis .                                                

The ordinary estimating methods is failed in dealing with data that consist of the presence of outlier values and hence on the absence of such that have undesirable effect on the result.    &nbs

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Publication Date
Wed Mar 13 2019
Journal Name
Al-khwarizmi Engineering Journal
Transient Behavior Analysis for Solar Energy Storage in PCM-CFM Material Using Equivalent Heat Capacity Method as Storage Model
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A paraffin wax and copper foam matrix were used as a thermal energy storage material in the double passes air solar chimney (SC) collector to get ventilation effect through daytime and after sunset. Air SC collector was installed in the south wall of an insulated test room and tested with different working angles (30o, 45o and 60o). Different SC types were used; single pass, double passes flat plate collector and double pass thermal energy storage box collector (TESB). A computational model based on the finite volume method for transient tw dimensional domains was carried out to describe the heat transfer and storage in the thermal energy storage material of collector. Also, equivalent specific heat metho

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