On Criteria for Testing Linear Hypotheses in Regression Models
An Application of RLS Estimators
(Sprache: Englisch)
In this present book Chapter I is an introductory one. It contains the general introduction about the importance of hypotheses testing in econometrics. Chapter II deals with the inferential aspects of linear models. It describes the various problems of the...
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In this present book Chapter I is an introductory one. It contains the general introduction about the importance of hypotheses testing in econometrics. Chapter II deals with the inferential aspects of linear models. It describes the various problems of the theory of Econometrics. Chapter III describes the existing criteria for testing general linear hypotheses in the linear models. It contains the derivation and applications of Restricted Least Squares estimation in the theory of Econometrics.Chapter IV proposes same alternative criteria for testing general linear hypotheses in the generalized linear models. Mean Squared Error (MSE) criteria have been explained for testing general linear hypotheses in the generalized linear models under the problems of heteroscedasticity and singular linear models.Chapter V gives the conclusions of the book .Several relavant articles regarding the Hypotheses testing in linear regression models have been presented under a title 'BIBLIOGRAPHY'
Bibliographische Angaben
- Autoren: N. Ramesh Kumar , Balasiddamuni Pagadala , A. V. Prasad
- 2014, 76 Seiten, Maße: 22 cm, Kartoniert (TB), Englisch
- Verlag: LAP Lambert Academic Publishing
- ISBN-10: 3659506664
- ISBN-13: 9783659506666
Sprache:
Englisch
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