The aim of this research does not deal with evaluation occurs at any points in the design of the plan alternatives themselves or formulation of goals and objectives. The aim of this research is that test and evaluate the fully alternatives. We can therefore state as the principle that evaluation of alternative plans must be based on attempts to show how far each plan satisfies all the objectives are expressed as specification of the performance of the urban and regional system. The planner can submit the result (as in the traditional way) for each alternative, with particular reference to the weighting of objectives. The summery result can be presented and the preferred plan indicated that with largest index of Goals-achievement. Although, this way suffers from main criticism: Does the observed differences between the alternatives represent statistically significant differences. The overriding need is to develop plan selection evaluative tools. This will be done by using difference statistical tests, which have been offered for plan selection.
In this paper we estimate the coefficients and scale parameter in linear regression model depending on the residuals are of type 1 of extreme value distribution for the largest values . This can be regard as an improvement for the studies with the smallest values . We study two estimation methods ( OLS & MLE ) where we resort to Newton – Raphson (NR) and Fisher Scoring methods to get MLE estimate because the difficulty of using the usual approach with MLE . The relative efficiency criterion is considered beside to the statistical inference procedures for the extreme value regression model of type 1 for largest values . Confidence interval , hypothesis testing for both scale parameter and regression coefficients
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Atorvastatin calcium (ATR) is an antihyperlipidemic agent used for lowering blood cholesterol levels. However, it is very slightly soluble in water with poor oral bioavailability, which interferes with its therapeutic action. It is classified as a class II drug according to Biopharmaceutical Classification System (low solubility and high permeability).
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