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The use of the Principal components and Partial least squares methods to estimate the parameters of the logistic regression model in the case of linear multiplication problem
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Abstract

  The logistic regression model is one of the nonlinear models that aims at obtaining highly efficient capabilities, It also the researcher an idea of the effect of the explanatory variable on the binary response variable.                                                                                                       

The large number of explanatory variables usually used to illustrate the response led to the problem of linear multiplicity between the explanatory variables that make estimating the parameters of the model not very accurate.                                                                                

In this paper, examined methods for estimating the parameters of the logistic regression model in the case of the problem of linear multiplicity These methods are: Principal components of logistic regression method and Partial least square regression method.                                                                                                                                       

The results of the simulation showed that the method (PCLR(3pc’s)) is best for estimating the parameters of the binary logistic regression model response in the case of a problem of linear multiplicity.                                                                                                                                 

 

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Publication Date
Wed Feb 06 2019
Journal Name
Journal Of The College Of Education For Women
The Effect use of the Internet in Academic Libraries A Case Study
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The aim of this research is to show the importance of the effective use
of the internet in academic libraries; to improve the services and to increase
the competence of librarians.
The research has given some recommendations to improve the quality
of services and the need for cooperative network among academic libraries.

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Publication Date
Sat Sep 30 2023
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Determinants of Investment Allocations in the Agricultural Sector in Iraq : A Comparison Between the Method of least Squares Approach and the errror Correction Model
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Abstract

                 The research aimed to test the relationship between the size of investment allocations in the agricultural sector in Iraq and their determinants using the Ordinary Least Squares (OLS) method compared to the Error Correction Model (ECM) approach. The time series data for the period from 1990 to 2021 was utilized. The analysis showed that the estimates obtained using the ECM were more accurate and significant than those obtained using the OLS method. Johansen's test indicated the presence of a long-term equilibrium relationship between the size of investment allocations and their determinants. The results of th

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Publication Date
Fri Aug 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Comparison between the Local Polynomial Kernel and Penalized Spline to Estimating Varying Coefficient Model
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Analysis the economic and financial phenomena and other requires to build the appropriate model, which represents the causal relations between factors. The operation building of the model depends on Imaging conditions and factors surrounding an in mathematical formula and the Researchers target to build that formula appropriately. Classical linear regression models are an important statistical tool, but used in a limited way, where is assumed that the relationship between the variables illustrations and response variables identifiable. To expand the representation of relationships between variables that represent the phenomenon under discussion we used Varying Coefficient Models

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Publication Date
Tue Dec 20 2011
Journal Name
المؤتمر الدولي الثالث للاحصائيين العرب
Use a form ARX(p,q) to estimate time series for the Iraqi Economy
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Due to the lack of statistical researches in studying with existing (p) of Exogenous Input variables, and there contributed in time series phenomenon as a cause, yielding (q) of Output variables as a result in time series field, to form conceptual idea similar to the Classical Linear Regression that studies the relationship between dependent variable with explanatory variables. So highlight the importance of providing such research to a full analysis of this kind of phenomena important in consumer price inflation in Iraq. Were taken several variables influence and with a direct connection to the phenomenon and analyzed after treating the problem of outliers existence in the observations by (EM) approach, and expand the sample size (n=36) to

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Publication Date
Fri Apr 13 2012
Journal Name
Kut Journal For Economic And Administrative Sciences
Using Different Methods to Estimate the Parameters of Probability Death Density Function with Application
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In this paper, the maximum likelihood estimates for parameter ( ) of two parameter's Weibull are studied, as well as white estimators and (Bain & Antle) estimators, also Bayes estimator for scale parameter ( ), the simulation procedures are used to find the estimators and comparing between them using MSE. Also the application is done on the data for 20 patients suffering from a headache disease.

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Publication Date
Mon Oct 22 2018
Journal Name
Journal Of Economics And Administrative Sciences
Using Mehar method to change fuzzy cost of fuzzy linear model with practical application
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  Many production companies suffers from big losses because of  high production cost and low profits for several reasons, including raw materials high prices and no taxes impose on imported goods also consumer protection law deactivation and national product and customs law, so most of consumers buy imported goods because it is characterized by modern specifications and low prices.

  The production company also suffers from uncertainty in the cost, volume of production, sales, and availability of raw materials and workers number because they vary according to the seasons of the year.

  I had adopted in this research fuzzy linear program model with fuzzy figures

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Publication Date
Thu Jun 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
The Use of the Regression Tree and the Support Vector Machine in the Classification of the Iraqi Stock Exchange for the Period 2019-2020
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 The financial markets are one of the sectors whose data is characterized by continuous movement in most of the times and it is constantly changing, so it is difficult to predict its trends , and this leads to the need of methods , means and techniques for making decisions, and that pushes investors and analysts in the financial markets to use various and different methods in order to reach at predicting the movement of the direction of the financial markets. In order to reach the goal of making decisions in different investments, where the algorithm of the support vector machine and the CART regression tree algorithm are used to classify the stock data in order to determine

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Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Comparison some of methods wavelet estimation for non parametric regression function with missing response variable at random
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Abstract

 The problem of missing data represents a major obstacle before researchers in the process of data analysis in different fields since , this problem is a recurrent one in all fields of study including social , medical , astronomical and clinical experiments .

The presence of such a problem within the data to be studied may influence negatively on the analysis and it may lead to misleading conclusions , together with the fact that these conclusions that result from a great bias caused by that problem in spite of the efficiency of wavelet methods but they are also affected by the missing of data , in addition to the impact of the problem of miss of accuracy estimation

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Publication Date
Tue Oct 23 2018
Journal Name
Journal Of Economics And Administrative Sciences
Processing of missing values in survey data using Principal Component Analysis and probabilistic Principal Component Analysis methods
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The idea of ​​carrying out research on incomplete data came from the circumstances of our dear country and the horrors of war, which resulted in the missing of many important data and in all aspects of economic, natural, health, scientific life, etc.,. The reasons for the missing are different, including what is outside the will of the concerned or be the will of the concerned, which is planned for that because of the cost or risk or because of the lack of possibilities for inspection. The missing data in this study were processed using Principal Component  Analysis and self-organizing map methods using simulation. The variables of child health and variables affecting children's health were taken into account: breastfeed

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Publication Date
Fri Apr 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
THE USE OF SIMULATION AND LINEAR PROGRAMMING IN THE PLANNING OF AUDIT WORK (An Empirical Study in the Office of Financial Supervision)
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Research includes three axes, the first is the average estimate time of achievement (day) to work oversight, to five supervisory departments in the Office of Financial Supervision Federal and then choose the three control outputs and at the level of each of the five departments above, and after analyzing the data statistically back to us that the distribution of the times of achievement It is the exponential distribution (Exponential Distribution) a parameter (q), and the distribution of normal (Normal Distribution) with two parameters (μ, σ2), and introduced four methods of parameter estimation (q) as well as four modalities parameter to estimate (

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