The performance of a condenser in a domestic refrigerator system without wires and a condenser with a novel design consisted of number of loops as elliptical shape is investigated experimentally in this work. The experiment was conducted with a refrigerator designed to work with HFC134a, under no load and with loads of (1.5,3 and 12 liters of water). In particular, the effects of shape change of the condenser were very important in heat transfer enhancement and reduce of the frictional loss as a result of reducing the pressure drop in the condenser. The results shown that compressor work decreases with elliptical condenser about (8.6% to 11.3%), and then the power consumption decreases also. The performance of household refrigerator with

In this research, the covariance estimates were used to estimate the population mean in the stratified random sampling and combined regression estimates. were compared by employing the robust variance-covariance matrices estimates with combined regression estimates by employing the traditional variance-covariance matrices estimates when estimating the regression parameter, through the two efficiency criteria (RE) and mean squared error (MSE). We found that robust estimates significantly improved the quality of combined regression estimates by reducing the effect of outliers using robust covariance and covariance matrices estimates (MCD, MVE) when estimating the regression parameter. In addition, the results of the simulation study proved

This paper deals with constructing mixed probability distribution from mixing exponential

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

Estimation of the tail index parameter of a one - parameter Pareto model has wide important by the researchers because it has awide application in the econometrics science and reliability theorem.

Here we introduce anew estimator of ^"generalized median" type and compare it with the methods of Moments and Maximum likelihood by using the criteria, mean square error.

 The estimator of generalized median type performing best over all.

Analysis the economic and financial phenomena and other requires to build the appropriate model, which represents the causal relations between factors. The operation building of the model depends on Imaging conditions and factors surrounding an in mathematical formula and the Researchers target to build that formula appropriately. Classical linear regression models are an important statistical tool, but used in a limited way, where is assumed that the relationship between the variables illustrations and response variables identifiable. To expand the representation of relationships between variables that represent the phenomenon under discussion we used Varying Coefficient Models

This research aims to estimate production functions through which production relations, possibilities for production elements substitution, measurement of its substitution elasticity, and efficiency and distribution coefficients can be analyzed. This would be done through estimation of constant elasticity of substitution production function for agricultural companies in Iraq depending on data from Iraqi Stock Exchange reports of 2005-2016. The researcher had used panel data model and estimated its three models: the Pooled Regression Model (PRM), the Fixed Effect Model (FEM) and the Random Effect Model (REM). A comparison was made for theses three models using F, LM, Husman tests. Tests show that Fixed Effect Model (FEM) is the best

The theory of probabilistic programming  may be conceived in several different ways. As a method of programming it analyses the implications of probabilistic variations in the parameter space of linear or nonlinear programming model. The generating mechanism of such probabilistic variations in the economic models may be due to incomplete information about changes in demand, pro­duction and technology, specification errors about the econometric relations presumed for different economic agents, uncertainty of various sorts and the consequences of imperfect aggregation or disaggregating of economic variables. In this Research we discuss the probabilistic programming problem when the coefficient b_i is random variable