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ESTIMATION OF COEFFICIENTS AND SCALE PARAMETER FOR LINEAR (TYPE 1) EXTREME VALUE REGRESSION MODEL FOR LARGEST VALUES WITH APPLICATIONS

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
Tue Mar 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Some Methods for Estimating Parameters of General Linear Model in Presence of Heteroscedastic Problem and High Leverage Points

Linear regression is one of the most important statistical tools through which it is possible to know the relationship between the response variable and one variable (or more) of the independent variable(s), which is often used in various fields of science. Heteroscedastic is one of the linear regression problems, the effect of which leads to inaccurate conclusions. The problem of heteroscedastic may be accompanied by the presence of extreme outliers in the independent variables (High leverage points) (HLPs), the presence of (HLPs) in the data set result unrealistic estimates and misleading inferences. In this paper, we review some of the robust

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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

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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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Economics And Administrative Sciences
Fuzzy Bridge Regression Model Estimating via Simulation

      The main problem when dealing with fuzzy data variables is that it cannot be formed by a model that represents the data through the method of Fuzzy Least Squares Estimator (FLSE) which gives false estimates of the invalidity of the method in the case of the existence of the problem of multicollinearity. To overcome this problem, the Fuzzy Bridge Regression Estimator (FBRE) Method was relied upon to estimate a fuzzy linear regression model by triangular fuzzy numbers. Moreover, the detection of the problem of multicollinearity in the fuzzy data can be done by using Variance Inflation Factor when the inputs variable of the model crisp, output variable, and parameters are fuzzed. The results were compared usin

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Compare Estimate Methods of Parameter to Scheffʼe Mixture Model By Using Generalized Inverse and The Stepwise Regression procedure for Treatment Multicollinearity Problem

Mixture experiments are response variables based on the proportions of component for this mixture. In our research we will compare the scheffʼe model with the kronecker model for the mixture experiments, especially when the experimental area is restricted.

     Because of the experience of the mixture of high correlation problem and the problem of multicollinearity between the explanatory variables, which has an effect on the calculation of the Fisher information matrix of the regression model.

     to estimate the parameters of the mixture model, we used the (generalized inverse ) And the Stepwise Regression procedure

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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

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
Mon Jun 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
Use of lower squares and restricted boxes In the estimation of the first-order self-regression parameter AR (1) (simulation study)

Use of lower squares and restricted boxes
In the estimation of the first-order self-regression parameter
AR (1) (simulation study)

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Publication Date
Thu Apr 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Estimate the Partial Linear Model Using Wavelet and Kernel Smoothers

This article aims to estimate the partially linear model by using two methods, which are the Wavelet and Kernel Smoothers. Simulation experiments are used to study the small sample behavior depending on different functions, sample sizes, and variances. Results explained that the wavelet smoother is the best depending on the mean average squares error criterion for all cases that used.

 

 

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Publication Date
Mon Oct 01 2012
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Serum Interleukin-6 level in children with type 1 diabetes mellitus

pancreatic islets in which a process of programmed cell death (apoptosis) is elicited in the β-cells by interaction of activated T-cells and proinflammatory cytokines in the immune infiltrate. Interleukin-6 (IL-6) is a pleiotropic cytokine with a key impact on both immunoregulation and nonimmune events in many cell types .
Objective: to assess the level of serum IL-6 as an inflammatory marker in type 1 diabetic children, with correlation to FBG and HbA1c.
Subjects and methods: 45 type 1 diabetic child (20 males and 25 females), mean age 10.9± 3.4 years who attended the National Diabetic Center, Al-Mustansiria university were included in this study. 45 apparently healthy controls matched for age and sex were participated in this s

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Publication Date
Sat Oct 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Bayesian Estimator for the Scale Parameter of the Normal Distribution Under Different Prior Distributions

In this study, we used Bayesian method to estimate scale parameter for the normal distribution. By considering three different prior distributions such as the square root inverted gamma (SRIG) distribution and the non-informative prior distribution and the natural conjugate family of priors. The Bayesian estimation based on squared error loss function, and compared it with the classical estimation methods to estimate the scale parameter for the normal distribution, such as the maximum likelihood estimation and th

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Publication Date
Thu May 11 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Modified Thompson –Type Testimators for the Parameters of Simple Linear Regression Model

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