Multiple linear regressions are concerned with studying and analyzing the relationship between the dependent variable and a set of explanatory variables. From this relationship the values of variables are predicted. In this paper the multiple linear regression model and three covariates were studied in the presence of the problem of auto-correlation of errors when the random error distributed the distribution of exponential. Three methods were compared (general least squares, M robust, and Laplace robust method). We have employed the simulation studies and calculated the statistical standard mean squares error with sample sizes (15, 30, 60, 100). Further we applied the best method on the real experiment data representing the varieties of

Radiation therapy plays an important role in improving breast cancer cases, in order to obtain an appropriateestimate of radiation doses number given to the patient after tumor removal; some methods of nonparametric regression werecompared. The Kernel method was used by Nadaraya-Watson estimator to find the estimation regression function forsmoothing data based on the smoothing parameter h according to the Normal scale method (NSM), Least Squared CrossValidation method (LSCV) and Golden Rate Method (GRM). These methods were compared by simulation for samples ofthree sizes, the method (NSM) proved to be the best according to average of Mean Squares Error criterion and the method(LSCV) proved to be the best according to Average of Mean Absolu

This study focuses on evaluating the suitability of three interpolation methods in terms of their accuracy at climate data for some provinces of south of Iraq. Two data sets of maximum and minimum temperature in February 2008 from nine meteorological stations located in the south of Iraq using three interpolation methods. ArcGIS is used to produce the spatially distributed temperature data by using IDW, ordinary kriging, and spline. Four statistical methods are applied to analyze the results obtained from three interpolation methods. These methods are RMSE, RMSE as a percentage of the mean, Model efficiency (E) and Bias, which showed that the ordinary krigingis the best for this data from other methods by the results that have b

This research aims to removes dyes from waste water by adsorption using banana peels. The conduct experiment done by banana powder and banana gel to compare between them and find out which one is the most efficient in adsorption. Studying the effects different factors on adsorption material and calculate the best removal efficiency to get rid of the methylene blue dye (MB).

Desert truffle is considered as a type of Syrian wild fungi that spreads heavily, and it occupies important rank in folk medicine, where its aqueous extract is used for the treatment of some eye and skin illnesses, and people prefer the use of black truffle. This work interested in studying of the most available species; Terfezia claveryi (black) and Tirmania pinoyi (white). The extracts of the two species of truffle were prepared by maceration with water, methanol, and ethanol 70%. Their total phenolic contents (TPC) and total flavonoid contents (TFC) were analyzed using Folin-ciocalteu and Aluminum chloride methods respectively, and their antioxidant activities was tested using 2,2-diphenyl-1-picrylhydrazyl (DPPH) and

In this paper, Bayes estimators of the parameter of Maxwell distribution have been derived along with maximum likelihood estimator. The non-informative priors; Jeffreys and the extension of Jeffreys prior information has been considered under two different loss functions, the squared error loss function and the modified squared error loss function for comparison purpose. A simulation study has been developed in order to gain an insight into the performance on small, moderate and large samples. The performance of these estimators has been explored numerically under different conditions. The efficiency for the estimators was compared according to the mean square error MSE. The results of comparison by MSE show that the efficiency of Bayes est

In this paper, Bayes estimators of the parameter of Maxwell distribution have been derived along with maximum likelihood estimator. The non-informative priors; Jeffreys and the extension of Jeffreys prior information has been considered under two different loss functions, the squared error loss function and the modified squared error loss function for comparison purpose. A simulation study has been developed in order to gain an insight into the performance on small, moderate and large samples. The performance of these estimators has been explored numerically under different conditions. The efficiency for the estimators was compared according to the mean square error MSE. The results of comparison by MSE show that the efficiency of B

Wireless sensor applications are susceptible to energy constraints. Most of the energy is consumed in communication between wireless nodes. Clustering and data aggregation are the two widely used strategies for reducing energy usage and increasing the lifetime of wireless sensor networks. In target tracking applications, large amount of redundant data is produced regularly. Hence, deployment of effective data aggregation schemes is vital to eliminate data redundancy. This work aims to conduct a comparative study of various research approaches that employ clustering techniques for efficiently aggregating data in target tracking applications as selection of an appropriate clustering algorithm may reflect positive results in the data aggregati