Inference in Linear Models With Auto Correlated Disturbances - Chalapathi Rao, M. V.;Pagadala, Balasiddamuni;Prabhakara Naik, J.
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In the Present Book Chapter-I is an introductory one. It contains the general introduction about the problem of autocorrelation . Chapter-II presents statistical inferential problems in linear models. It explains the specification of classical linear regression model together with its estimation. Chapter-III describes the review about inferential methods in linear models under the problem of autocorrelation. Chapter-IV proposes some alternative inferential methods for linear model with autocorrelated disturbances. It uses the various types of residuals such as ordinary least squares,…mehr

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Produktbeschreibung
In the Present Book Chapter-I is an introductory one. It contains the general introduction about the problem of autocorrelation . Chapter-II presents statistical inferential problems in linear models. It explains the specification of classical linear regression model together with its estimation. Chapter-III describes the review about inferential methods in linear models under the problem of autocorrelation. Chapter-IV proposes some alternative inferential methods for linear model with autocorrelated disturbances. It uses the various types of residuals such as ordinary least squares, studentized and predicted residuals to develop alternative iterative estimation methods and tests for the autocorrelation. Chapter-V depicts the conclusions. Several selected references for the present book are given under the title 'BIBLIOGRAPHY'
Autorenporträt
He is Presently working as a Reader in Jawahar Bharati Degree/P.G College (NACC-A Grade & CPE),Kavali.He has 27 years Teaching & Research Experience in the Field of Statistics.He Presented Several Research Papers Many more Conferences in all over India.He published Several Articles in Many Reputed Journals.