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.

Magnesium aluminum silicate of glass ceramic having different amounts of magnesium fluoride in the range (0-13.2)%. Thermal expansion coefficient and micro hardness of the base glass and glass ceramic samples are seen to be interdependent but due to the multi – component system, the behaviour is seen to be somewhat complex, with an increase in Mg F2 content. The thermal expansion coefficient increase and micro harness decrease, numerical simulation of thermal expansion and hardness is useful in this study, L2 – regression is used to calculate the two parameters associated with each glass component, by comparing the measured parameters and the calculated parameters ,it is useful to use such a method to calculate the quantity

In this paper, we derived an estimator of reliability function for Laplace distribution with two parameters using Bayes method with square error loss function, Jeffery’s formula and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived Bayesian estimator compared to the maximum likelihood of this function and moment method using simulation technique by Monte Carlo method under different Laplace distribution parameters and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator and moment estimator in all samples sizes

Poverty phenomenon is very substantial topic that determines the future of societies and governments and the way that they deals with education, health and economy. Sometimes poverty takes multidimensional trends through education and health. The research aims at studying multidimensional poverty in Iraq by using panelized regression methods, to analyze Big Data sets from demographical surveys collected by the Central Statistical Organization in Iraq. We choose classical penalized regression method represented by The Ridge Regression, Moreover; we choose another penalized method which is the Smooth Integration of Counting and Absolute Deviation (SICA) to analyze Big Data sets related to the different poverty forms in Iraq. Euclidian Distanc

Abstract

          Binary logistic regression model used in data classification and it is the strongest most flexible tool in study cases variable response binary when compared to linear regression. In this research, some classic methods were used to estimate parameters binary logistic regression model, included the maximum likelihood method, minimum chi-square method, weighted least squares, with bayes estimation , to choose the best method of estimation by default values to estimate parameters according two different models of general linear regression models ,and different s

In this paper, we will illustrate a gamma regression model assuming that the dependent variable (Y) is a gamma distribution and that it's mean ( ) is related through a linear predictor with link function which is identity link function g(μ) = μ. It also contains the shape parameter which is not constant and depends on the linear predictor and with link function which is the log link and we will estimate the parameters of gamma regression by using two estimation methods which are The Maximum Likelihood and the Bayesian and a comparison between these methods by using the standard comparison of average squares of error (MSE), where the two methods were applied to real da

 The objective of this study is to select a suitable observing region at Baghdad location (44^o 22^' 48^", 33^o 16^' 30^") with low interference that may affect frequency of 1.42 GHz. Baghdad University Radio Telescope (BURT) is used in this study to determine a convenient region for observation in Baghdad sky. Different azimuths and elevations were chosen at different observations time. The results of this study showed that the best observations regions were located at azimuth (120^o-160^o) and (210^o-260^o). These regions included less sky temperature and estimated to be (42.8 to 163) K. The sky temperature model could be represente

  Abstract

      The nuclear structure of ^28-40Si isotopes toward neutron dripline has been investigated in framework of shell model with Skyrme-Hrtree-Fock method using certain Skyrme parameterizations. Moreover, investigations of static properties such as nuclear densities for proton, neutron, mass, and, charge densities with their corresponding rms radii, neutron skin thicknesses, binding energies, separation energies, shell gap, and pairing gap have been performed using the most recent Skyrme parameterization. The calculated results have been compared with available experimental data to identify which of these parameterizations introduced equivalent results with the ex

The electric quadrupole moments for some scandium isotopes (41, 43, 44, 45, 46, 47Sc) have been calculated using the shell model in the proton-neutron formalism. Excitations out of major shell model space were taken into account through a microscopic theory which is called core polarization effectives. The set of effective charges adopted in the theoretical calculations emerging about the core polarization effect. NushellX@MSU code was used to calculate one body density matrix (OBDM). The simple harmonic oscillator potential has been used to generate the single particle matrix elements. Our theoretical calculations for the quadrupole moments used the two types of effective interactions to obtain the best interaction compared with the exp

This paper  deals  to how to estimate points non measured spatial data when the number of its terms (sample spatial) a few, that are not preferred for the estimation process, because we also know that whenever if the data is large, the estimation results of the points non measured to be better and thus the variance estimate less, so the idea of this paper is how to take advantage of the data other secondary (auxiliary), which have a strong correlation with the primary data (basic) to be estimated single points of non-measured, as well as measuring the variance estimate, has been the use of technique Co-kriging in this field to build predictions spatial estimation process, and then we applied this idea to real data in th