Biased Estimation Methods with Autocorrelation using Simulation : Problem of Multicoolinearity and Autocorrelation

Language: English

Published by LAP LAMBERT Academic Publishing, 2011

3844324763 / 9783844324761

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nach der Bestellung gedruckt Neuware - Printed after ordering - 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.

Seller Inventory # 9783844324761

Title
Biased Estimation Methods with Autocorrelation using Simulation : Problem of Multicoolinearity and Autocorrelation
Author
Hussein Eledum
Publisher
LAP LAMBERT Academic Publishing
Publication year
2011
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
3844324763
ISBN 13
9783844324761
Item weight
316 grams
Dimensions
220x150x13 mm

AHA-BUCH GmbH

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