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jeasiq-1455
CALCULATION BIASES FOR COEFFICIENTS AND SCALE PARAMETER FOR LINEAR (TYPE 1) EXTREME VALUE REGRESSION MODEL FOR LARGEST VALUES
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Abstract

Characterized by the Ordinary Least Squares (OLS) on Maximum Likelihood for the greatest possible way that the exact moments are known , which means that it can be found, while the other method they are unknown, but approximations to their biases correct to 0(n-1) can be obtained by standard methods. In our research expressions for approximations to the biases of the ML estimators (the regression coefficients and scale parameter) for linear (type 1) Extreme Value Regression Model for Largest Values are presented by using the advanced approach depends on finding the first derivative, second and third.

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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
Fri Dec 20 2024
Journal Name
Al-rafidain University College For Sciences
“Simple Regression Analysis by using Linear Programming Technique and illustration of Absolute Residuals method with another Estimation Techniques”
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This research deals with unusual approach for analyzing the Simple Linear Regression via Linear Programming by Two - phase method, which is known in Operations Research: “O.R.”. The estimation here is found by solving optimization problem when adding artificial variables: Ri. Another method to analyze the Simple Linear Regression is introduced in this research, where the conditional Median of (y) was taken under consideration by minimizing the Sum of Absolute Residuals instead of finding the conditional Mean of (y) which depends on minimizing the Sum of Squared Residuals, that is called: “Median Regression”. Also, an Iterative Reweighted Least Squared based on the Absolute Residuals as weights is performed here as another method to

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Publication Date
Wed Jun 29 2022
Journal Name
Journal Of Al-rafidain University College For Sciences ( Print Issn: 1681-6870 ,online Issn: 2790-2293 )
The Use Of Genetic Algorithm In Estimating The Parameter Of Finite Mixture Of Linear Regression
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The estimation of the parameters of linear regression is based on the usual Least Square method, as this method is based on the estimation of several basic assumptions. Therefore, the accuracy of estimating the parameters of the model depends on the validity of these hypotheses. The most successful technique was the robust estimation method which is minimizing maximum likelihood estimator (MM-estimator) that proved its efficiency in this purpose. However, the use of the model becomes unrealistic and one of these assumptions is the uniformity of the variance and the normal distribution of the error. These assumptions are not achievable in the case of studying a specific problem that may include complex data of more than one model. To

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Publication Date
Sat Jun 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Compared Some Estimators Ordinary Ridge Regression And Bayesian Ridge Regression With Practical Application
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Maulticollinearity is a problem that always occurs when two or more predictor variables are correlated with each other. consist of the breach of one basic assumptions of the ordinary least squares method with biased estimates results, There are several methods which are proposed to handle this problem including the  method To address a problem  and  method To address a problem , In this research a comparisons are employed between the biased   method and unbiased   method with Bayesian   using Gamma distribution  method  addition to Ordinary Least Square metho

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Publication Date
Thu Feb 17 2022
Journal Name
Journal Of Discrete Mathematical Sciences And Cryptography
Calculation for the groups
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Publication Date
Thu Jul 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Bayesian Approach for estimating the unknown Scale parameter of Erlang Distribution Based on General Entropy Loss Function
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We are used Bayes estimators for unknown scale parameter  when shape Parameter  is known of Erlang distribution. Assuming different informative priors for unknown scale  parameter. We derived The posterior density with posterior mean and posterior variance using different informative priors for unknown scale parameter  which are the inverse exponential distribution, the inverse chi-square distribution, the inverse Gamma distribution, and the standard Levy distribution as prior. And we derived Bayes estimators based on the general entropy loss function (GELF) is used the Simulation method to obtain the results. we generated different cases for the parameters of the Erlang model, for different sample sizes. The estimates have been comp

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Publication Date
Wed Oct 01 2014
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Growth Indices among Children and Adolescents with Type 1 Diabetes - Baghdad – Iraq, 2013
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Background: Type 1 diabetes mellitus is one of the most common chronic endocrine disorders of childhood, growth impairment is one of its long−term consequences

Objective: To study the anthropometric indices among children with type 1diabetes.
Results:
A total of 253 children with type 1diabetes were studied, 51.8% were females, 47.9% developed the disease at 5-9 years of age, and 52.6% presented with classical signs and symptoms. Stunting /sever stunting was 15% with male predominance, higher among older age group (10-20 y), wasting/ sever wasting was 19.4% with male predominance, higher among older age group (10-20 y), over weight/ obese was 3.6% with females predominant an

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Publication Date
Thu Mar 30 2023
Journal Name
Iraqi Journal Of Science
Determination of the Mathematical Model for Plasma Electronic Coefficients of the Earth's Ionosphere
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In this research, electron coefficients such as total collision frequency (colt/N), total ionization frequency (viz/N), and Power (P/N) for different gases such as (Ar, He, N2 and O2 (in Earth’s ionosphere have been calculated by applying the Boltzmann equation utilizing BOLSIG +, and it has been discovered that there is a significant impact of reducing the electric field (E/N) on electronic coefficients under which (E/N) increases. In addition, influence of (E/N) on electronic coefficients was studied. Reducing the electric field was chosen in the restricted range (1-100) Td, and the electronic coefficients for gases in the limited range (50-2000) km of the Earth's ionosphere. A positive correlation has been explained between all the

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Publication Date
Sun Jan 14 2024
Journal Name
Journal Of Al-rafidain University College For Sciences ( Print Issn: 1681-6870 ,online Issn: 2790-2293 )
Using Nonparametric Procedure to Develop an OCMT Estimator for Big Data Linear Regression Model with Application Chemical Pollution in the Tigris River
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Chemical pollution is a very important issue that people suffer from and it often affects the nature of health of society and the future of the health of future generations. Consequently, it must be considered in order to discover suitable models and find descriptions to predict the performance of it in the forthcoming years. Chemical pollution data in Iraq take a great scope and manifold sources and kinds, which brands it as Big Data that need to be studied using novel statistical methods. The research object on using Proposed Nonparametric Procedure NP Method to develop an (OCMT) test procedure to estimate parameters of linear regression model with large size of data (Big Data) which comprises many indicators associated with chemi

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Publication Date
Mon Sep 23 2019
Journal Name
Baghdad Science Journal
Hazard Rate Estimation Using Varying Kernel Function for Censored Data Type I
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     In this research, several estimators concerning the estimation are introduced. These estimators are closely related to the hazard function by using one of the nonparametric methods namely the kernel function for censored data type with varying bandwidth and kernel boundary. Two types of bandwidth are used:  local bandwidth and global bandwidth. Moreover, four types of boundary kernel are used namely: Rectangle, Epanechnikov, Biquadratic and Triquadratic and the proposed function was employed with all kernel functions. Two different simulation techniques are also used for two experiments to compare these estimators. In most of the cases, the results have proved that the local bandwidth is the best for all the

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