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'
| Autorius: | M. V. Chalapathi Rao, Balasiddamuni Pagadala, J. Prabhakara Naik, |
| Leidėjas: | LAP LAMBERT Academic Publishing |
| Išleidimo metai: | 2014 |
| Knygos puslapių skaičius: | 144 |
| ISBN-10: | 3659504033 |
| ISBN-13: | 9783659504037 |
| Formatas: | 220 x 150 x 9 mm. Knyga minkštu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „Inference in Linear Models With Auto Correlated Disturbances: Iterative Estimation for Autoregressive models“
