In this paper, we are mainly concerned with estimating cascade reliability model (2+1) based on inverted exponential distribution and comparing among the estimation methods that are used . The maximum likelihood estimator and uniformly minimum variance unbiased estimators are used to get  of the strengths  and the stress ;k=1,2,3 respectively then, by using the unbiased estimators, we propose Preliminary test single stage shrinkage (PTSSS) estimator when a prior knowledge is available for the scale parameter as initial value due past experiences . The Mean Squared Error [MSE] for the proposed estimator is derived to compare among the methods. Numerical results about conduct of the considered

The problem of rapid population growth is one of the main problems effecting countries of the world the reason for this the growth in different environment areas of life commercial, industrial, social, food and educational. Therefore, this study was conducted on the amount of potable water consumed using two models of the two satellite and aerial images of the Kadhimiya District-block 427 and Al-Shu^,laa district-block 450 in Baghdad city for available years in the Secretariat of Baghdad (2005, 2011,2013,2015). Through the characteristics of geographic information systems, which revealed the spatial patterns of urban creep by determining the role and buildings to be created, which appear in the picture for the

An adaptive fuzzy weighted linear regression model in which the output is based
on the position and entropy of quadruple fuzzy numbers had dealt with. The solution
of the adaptive models is established in terms of the iterative fuzzy least squares by
introducing a new suitable metric which takes into account the types of the influence
of different imprecisions. Furthermore, the applicability of the model is made by
attempting to estimate the fuzzy infant mortality rate in Iraq using a selective set of
inputs.

  In this paper simulation technique plays a vital role to compare between two approaches Maximum Likelihood method and Developed Least Square method to estimate the parameters of Frechet Poisson Lindley Distribution Compound. by coding using Matlab software program. Also, under different sample sizes via mean square error. As the results which obtain that Maximum Likelihood Estimation method is better than Developed Least Square method to estimate these parameters to the proposed distribution.

In this paper, two new simple, fast and efficient block matching algorithms are introduced, both methods begins blocks matching process from the image center block and moves across the blocks toward image boundaries. With each block, its motion vector is initialized using linear prediction that depending on the motion vectors of its neighbor blocks that are already scanned and their motion vectors are assessed. Also, a hybrid mechanism is introduced, it depends on mixing the proposed two predictive mechanisms with Exhaustive Search (ES) mechanism in order to gain matching accuracy near or similar to ES but with Search Time ST less than 80% of the ES. Also, it offers more control capability to reduce the search errors. The experimental tests

The problem of Multicollinearity is one of the most common problems, which deal to a large extent with the internal correlation between explanatory variables. This problem is especially Appear in economics and applied research, The problem of Multicollinearity has a negative effect on the regression model, such as oversized variance degree and estimation of parameters that are unstable when we use the Least Square Method ( OLS), Therefore, other methods were used to estimate the parameters of the negative binomial model, including the estimated Ridge Regression Method and the Liu type estimator, The negative binomial regression model is a nonline

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

 This paper is concerned with preliminary test single stage shrinkage estimators for the mean (q) of normal distribution with known variance s2 when a prior estimate (q0) of the actule value (q) is available, using specifying shrinkage weight factor y( ) as well as pre-test region (R).         Expressions for the Bias, Mean Squared Error [MSE( )] and Relative Efficiency [R.Eff.( )] of proposed estimators are derived. Numerical results and conclusions are drawn about selection different constants including in these expressions. Comparisons between suggested estimators with respect to usual estimators in the sense of Relative Efficiency are given. Furthermore, comparisons with the earlier existi

In this paper, Bayes estimators for the shape and scale parameters of Gamma distribution under the Entropy loss function have been obtained, assuming Gamma and Exponential priors for the shape and scale parameters respectively. Moment, Maximum likelihood estimators and Lindley’s approximation have been used effectively in Bayesian estimation. Based on Monte Carlo simulation method, those estimators are compared depending on the mean squared errors (MSE’s). The results show that, the performance of the Bayes estimator under Entropy loss function is better than other estimates in all cases.