A simulation study is used to examine the robustness of some estimators on a multiple linear regression model with problems of multicollinearity and non-normal errors, the Ordinary least Squares (LS) ,Ridge Regression, Ridge Least Absolute Value (RLAV), Weighted Ridge (WRID), MM and a robust ridge regression estimator MM estimator, which denoted as RMM this is the modification of the Ridge regression by incorporating robust MM estimator . finialy, we show that RMM is the best among the other estimators

Four local hemolysin producer bacterial isolates were selected, tow of them gram negative bacteria (Escherichia coli ,Pseudomonas aeruginosa ) and the other two were gram positive bacteria (Staphylococcus aureus , Bacillus cereus ). Minimum inhibitory concentration of the aqueous and alcoholic extracts of Punica granatum L. pericarp were determined towards the four bacterial isolates ,results obtaind showed that MICs of the aqueous extract were 200 mg/ml for E .coli and P. aeruginosa isolates while were 5 mg/ml and 2 mg/ml for B. cereus, S. aureus , respectively The MICs for the ethanolic extract were 50 mg/ml , 20 mg/ml ,1 mg/ml ,0.5 mg/ml for E. coli ,P. aeruginosa ,B. cereus ,S. aureus , respectively. The effect of Sub-MICs o

Gross domestic product (GDP) is an important measure of the size of the economy's production. Economists use this term to determine the extent of decline and growth in the economies of countries. It is also used to determine the order of countries and compare them to each other. The research aims at describing and analyzing the GDP during the period from 1980 to 2015 and for the public and private sectors and then forecasting GDP in subsequent years until 2025. To achieve this goal, two methods were used: linear and nonlinear regression. The second method in the time series analysis of the Box-Jenkins models and the using of statistical package (Minitab17), (GRETLW32)) to extract the results, and then comparing the two methods, T

Multilateral wells require a sophisticated type of well model to be applied in reservoir simulators to represent them. The model must be able to determine the flow rate of each fluid and the pressure throughout the well. The production rate calculations are very important because they give an indication about some main issues associated with multi-lateral wells such as one branch may produce water or gas before others, no production rate from one branch, and selecting the best location of a new branch for development process easily.                                &nbsp

Some methods recommended abroad to control the oriental hornet, Vespa orientalis L., attacking the honey bee, Apis mellifera L., colonies were tested, with some modifications, for the first time under the Iraqi conditions. One of these methods was carried out by covering the hive entrance with a piece of queen excluder to prevent the hornet from entering the hive. Also, the position of hive stand was reversed to deprive the hornet from using the flight board as a stage for waiting and creeping toward the defending bees. The second method was carried out by fixing a cardboard cone as a bee passage at the hive entrance to hinder the entry of the hornet into the hive. Both of these methods were found to be unsuccessful to

In this study, we focused on the random coefficient estimation of the general regression and Swamy models of panel data. By using this type of data, the data give a better chance of obtaining a better method and better indicators. Entropy's methods have been used to estimate random coefficients for the general regression and Swamy of the panel data which were presented in two ways: the first represents the maximum dual Entropy and the second is general maximum Entropy in which a comparison between them have been done by using simulation to choose the optimal methods.

The results have been compared by using mean squares error and mean absolute percentage error to different cases in term of correlation valu

In order to obtain a mixed model with high significance and accurate alertness, it is necessary to search for the method that performs the task of selecting the most important variables to be included in the model, especially when the data under study suffers from the problem of multicollinearity as well as the problem of high dimensions. The research aims to compare some methods of choosing the explanatory variables and the estimation of the parameters of the regression model, which are Bayesian Ridge Regression (unbiased) and the adaptive Lasso regression model, using simulation. MSE was used to compare the methods.

This deals with estimation of Reliability function and one shape parameter (?) of two- parameters Burr – XII , when ?(shape parameter is known) (?=0.5,1,1.5) and also the initial values of (?=1), while different sample shze n= 10, 20, 30, 50) bare used. The results depend on empirical study through simulation experiments are applied to compare the four methods of estimation, as well as computing the reliability function . The results of Mean square error indicates that Jacknif estimator is better than other three estimators , for all sample size and parameter values