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In the Present book Chapter I is an introductory one. It contains
the general introduction about the problem of heteroscedasticity.
Chapter II describes some aspects of linear models with their
inferential problems. It deals with some basic statistical results
about Gauss-Markov linear model besides the restricted least
squares estimation and its application to the tests of general
linear hypotheses. Chapter III presents a brief review on the
existing estimation methods for linear models under the various
specifications of heteroscedastic variances. Chapter IV deals with
the analysis and examination of different types of residuals with
their applications in the regression analysis. It also contains the
restricted residuals in 'Seemingly Unrelated Regression' (SUR)
systems. Chapter V proposes some new estimation procedures for
linear models under heteroscedasticity. Chapter VI depicts the
conclusions .Several references articles regarding the estimation
for linear models under heteroscedasticity have been presented
under a title "BIBLIOGRAPHY."
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