Biased Estimation Methods with Autocorrelation using Simulation - Eledum, Hussein
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The ordinary Least Squares method is considered as one of the most important way of estimating the parameters of the general linear model because of it's ease and simplicity and because of rationality of the results obtained when the specific assumptions are achieved regarding the general linear model . One of these assumptions is that the value of the error term in time is independent on its own preceding value or values E(Ut Ut-s) = 0 s 0 if this assumption does not hold then we have problem of autocorrelation . The other assumption is that the explanatory variables in the model are…mehr

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Produktbeschreibung
The ordinary Least Squares method is considered as one of the most important way of estimating the parameters of the general linear model because of it's ease and simplicity and because of rationality of the results obtained when the specific assumptions are achieved regarding the general linear model . One of these assumptions is that the value of the error term in time is independent on its own preceding value or values E(Ut Ut-s) = 0 s 0 if this assumption does not hold then we have problem of autocorrelation . The other assumption is that the explanatory variables in the model are orthogonal [R(x) = p+1 n ] if this assumption does not hold then we have problem of multicollinearity. In this book we will try to discuss these two problems simultaneously.
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Autorenporträt
Date of Birth: Jan 1, 1969 Nationality: Sudan Current position: Assistant Professor Assistant Professor, Department of Mathematics-Faculty of Science- Taibah University. (April 2010 - Present). Assistant Professor, Department of Statistics and Computer - Faculty of Science ¿Shendi University (Aug. 2005 - March. 2010).