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Estimation of Linear Models Under Heteroscedasticity: Inference with Heteroscedastic Errors - Tapa blanda

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

 
9783659503450: Estimation of Linear Models Under Heteroscedasticity: Inference with Heteroscedastic Errors
Tapa blanda
ISBN 10: 3659503452 ISBN 13: 9783659503450
Editorial: LAP LAMBERT Academic Publishing, 2014

Sinopsis

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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Reseña del editor

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".

Biografía del autor

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.

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Editorial
LAP LAMBERT Academic Publishing
Año de publicación
2014
Idioma
Inglés
ISBN 10 
3659503452
ISBN 13 
9783659503450
Encuadernación
Tapa blanda
Número de páginas
164
Contacto del fabricante
no disponible
Persona responsable
no disponible