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A Minimum Quadratic Unbiased Estimation (Minque) Of Parameters In A Linear Regression Model With Sperical Disturbances
[Full Text]
AUTHOR(S)
Prof. P. Balasiddamuni, Dr. K. KiranPrakash, Dr. C. L. Kantha Rao, Mr. A. Venkata Prasad, Prof. R. Abbaiah, Mr. G. Mokesh Rayalu.
KEYWORDS
Index terms: Heteroscedasticity, Homoscedastic, Minimum Quadratic Unbiased Estimation (MINQUE)
ABSTRACT
Abstract:- The present study considered the familiar Gauss-Markov linear model Y = X + in which the error vector has a zero mean vector and a covariance matrix , a diagonal matrix whose ith element is , the variance of ith observation Yi. Rao (1970) has suggested that the MINQUE theory for the vector of these heteroscedastic variances. In the present work, it has been assumed that the variance of error term will be a linear combination of certain independent variables i.e., = . Under this assumption the heteroscedastic variances and the parameters of the linear model have hence been estimated by using MINQUE theory.
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