Estimation of Linear Models Under Heteroscedasticity: Inference with Heteroscedastic Errors - Couverture souple

Prasad, R.V.S.; Pagadala, Balasiddamuni; Kantha Rao, C.L.

 
9783659503450: Estimation of Linear Models Under Heteroscedasticity: Inference with Heteroscedastic Errors
Couverture souple
ISBN 10 : 3659503452 ISBN 13 : 9783659503450
Editeur : LAP LAMBERT Academic Publishing, 2014

Synopsis

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”.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

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”.

Biographie de l'auteur

Dr. R.V.S. Prasad is a Associate Professor of Statistics & Principal, S.V.G.S Degree College, Nellore, A. P. State, India. He has 29 years of Teaching and Research Experience. He published 6 books,13 articles in International Journals. He presented 20 research papers in various National/International Conferences, Seminars and Symposiums.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2014
Langue
anglais
ISBN 10 
3659503452
ISBN 13 
9783659503450
Reliure
Broché
Nombre de pages
164
Coordonnées du fabricant
non disponible
Personne responsable
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