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ESTIMATION OF COEFFICIENTS AND SCALE PARAMETER FOR LINEAR (TYPE 1) EXTREME VALUE REGRESSION MODEL FOR LARGEST VALUES WITH APPLICATIONS
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In this paper we estimate the coefficients and scale parameter in linear regression model depending on the residuals are of type 1 of extreme  value distribution for the largest values . This can be regard as an improvement for the studies with the smallest values . We study two estimation methods ( OLS  & MLE ) where we resort to Newton – Raphson (NR) and Fisher Scoring methods to get MLE estimate because the difficulty of using the usual approach with MLE . The relative efficiency criterion is considered beside to the statistical inference procedures for the extreme value regression model of type 1 for largest values . Confidence interval , hypothesis testing for both scale parameter and regression coefficients , goodness of fit statistics based on the observed residuals are considered . As a conclusion and  through the probability plot test we get no evidence against using the assumed residuals distribution.

 

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Publication Date
Mon Jun 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
Estimation of the average sample size and defective ratio In a finite individualized inspection with a practical application
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The purpose of this research is to find the estimator of the average proportion of defectives based on attribute samples. That have been curtailed either with rejection of a lot finding the kth defective or with acceptance on finding the kth non defective.

The MLE (Maximum likelihood estimator) is derived. And also the ASN in Single Curtailed Sampling has been derived and we obtain a simplified Formula All the Notations needed are explained.

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Publication Date
Thu Oct 31 2019
Journal Name
Journal Of Engineering And Applied Sciences
Comparison of Estimate Methods of Multiple Linear Regression Model with Auto-Correlated Errors when the Error Distributed with General Logistic
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In this research, we studied the multiple linear regression models for two variables in the presence of the autocorrelation problem for the error term observations and when the error is distributed with general logistic distribution. The auto regression model is involved in the studying and analyzing of the relationship between the variables, and through this relationship, the forecasting is completed with the variables as values. A simulation technique is used for comparison methods depending on the mean square error criteria in where the estimation methods that were used are (Generalized Least Squares, M Robust, and Laplace), and for different sizes of samples (20, 40, 60, 80, 100, 120). The M robust method is demonstrated the best metho

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Publication Date
Thu Oct 31 2019
Journal Name
Journal Of Engineering And Applied Sciences
Comparison of Estimate Methods of Multiple Linear Regression Model with Auto-Correlated Errors when the Error Distributed with General Logistic
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In this research, we studied the multiple linear regression models for two variables in the presence of the autocorrelation problem for the error term observations and when the error is distributed with general logistic distribution. The auto regression model is involved in the studying and analyzing of the relationship between the variables, and through this relationship, the forecasting is completed with the variables as values. A simulation technique is used for comparison methods depending

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Publication Date
Wed Aug 09 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Comparison of Optimum Balance Values For Different Coefficients of Spherical Aberration of Optical System Including Different Apertures
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         The optimum balance values for different coefficient of spherical aberration (third and fifth degree also focal shift) were studied, the optical system includes different apertures (circle, ellipse, square and triangle) using point spread function (PSF).       By using (Marechal) method; the minimum value of mean square of variance in wave front was founded, so we can get the maximum of central intensity according to (Strehl) criterion.

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Publication Date
Tue Aug 18 2020
Journal Name
Journal Of Mechanics Of Continua And Mathematical Sciences
THE COMPARISON OF THE METHODS ESTIMATING THE FRACTIONAL DIFFERENCES OF PARAMETER AND ITS DEPENDENCE ON ESTIMATION THE BEST LINEAR MODEL OF TIME SERIES IN THE ENVIRONMENTAL FIELD
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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
Sat Dec 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
Finding the best estimation of generalized for failure rates by using Simulation
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The statistical distributions study aimed to obtain on best descriptions  of variable sets phenomena, which each of them got one behavior of that distributions .  The estimation operations study for that distributions considered of important things which could n't canceled in variable behavior study, as result  this research came as trial for reaching to best method for information distribution estimation which is generalized linear failure rate distribution, throughout studying the theoretical sides by depending on statistical posteriori methods  like greatest ability, minimum squares method and Mixing method (suggested method).        

The research

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Publication Date
Tue Mar 01 2022
Journal Name
International Journal Of Nonlinear Analysis And Applications
Semi-parametric regression function estimation for environmental pollution with measurement error using artificial flower pollination algorithm
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Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing flower pollination algorithm in the environmental field to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement. We estimate the regression function of the semi-parametric model by estimating the parametric model and estimating the non-parametric model, the parametric model is estimated by using an instrumental variables method (Wald method, Bartlett’s method, and Durbin

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Publication Date
Thu Jan 11 2018
Journal Name
Al-khwarizmi Engineering Journal
The Linear and Nonlinear Electro-Mechanical Fin Actuator
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Electromechanical actuators are used in a wide variety of aerospace applications such as missiles, aircrafts and spy-fly etc. In this work a linear and nonlinear fin actuator mathematical model has been developed and its response is investigated by developing an algorithm for the system using MATLAB. The algorithm used to the linear model is the state space algorithm while the algorithm used to the nonlinear model is the discrete algorithm. The huge moment constant is varied from (-3000 to 3000) and the damping ratio is varied from (0.4 to 0.8).        

 The comparison between linear and nonlinear fin actuator response results shows that for linear model, the maximum overshoot is about 10%,

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Publication Date
Fri Dec 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Compare Linear Progamming With Other Methods to Finding Optimal Solution for Transportation Problem
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The researcher studied transportation problem because it's great importance in the country's economy. This paper which ware studied several ways to find a solution closely to the optimization, has applied these methods to the practical reality by taking one oil derivatives which is benzene product, where the first purpose of this study is, how we can reduce the total costs of transportation for product of petrol from warehouses in the province of Baghdad, to some stations in the Karsh district and Rusafa in the same province. Secondly, how can we address the Domandes of each station by required quantity which is depending on absorptive capacity of the warehouses (quantities supply), And through r

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