On Criteria for Testing Linear Hypotheses in Regression Models Год выпуска: 2014Автор: N. Ramesh Kumar,Balasiddamuni Pagadala and A.V. PrasadИздательство: LAP Lambert Academic PublishingСтраниц: 76ISBN: 9783659506666Описание 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’
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Юлия Спасибо огромное! Прочитала вывод, очень хорошо сформулирован. Надеюсь преподаватель это оценит
