Title
Biased Estimation Methods with Autocorrelation using Simulation: Problem of Multicoolinearity and Autocorrelation,Used
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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 Uts) = 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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Warranty
We provide a 2-year limited warranty, from the date of purchase for all our products.
If you believe you have received a defective product, or are experiencing any problems with your product, please contact us.
This warranty strictly does not cover damages that arose from negligence, misuse, wear and tear, or not in accordance with product instructions (dropping the product, etc.).
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