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Inference in General Statistical Models: Estimated Gls Estimation Balasiddamuni Pagadala
Inference in General Statistical Models: Estimated Gls Estimation
Balasiddamuni Pagadala
In this book, an attempt has been made by proposing some new inferential procedures for linear regression models with different autoregressive schemes for disturbances. These estimation procedures have used iterative methods based on studentized residuals. It proposes some new inferential methods for linear statistical models with first, second and fourth order autoregressive disturbances. A new estimated iterative restricted GLS estimator has been derived for linear regression model with first order autoregressive disturbances. Later it has been applied for testing the general linear hypothesis. The linear statistical models have been specified with AR (1), AR (2) and AR (4) disturbances. The EGLS methods of estimation have been developed with particular AR (2) and AR (4) disturbances by using Iterative procedures. Here, Studentized residuals have been used in the place of OLS residuals. The parametric tests for particular second order and fourth order autocorrelations also have been discussed in this book
| Médias | Livres Paperback Book (Livre avec couverture souple et dos collé) |
| Validé | 12 août 2013 |
| ISBN13 | 9783659389771 |
| Éditeurs | LAP LAMBERT Academic Publishing |
| Pages | 196 |
| Dimensions | 150 × 11 × 226 mm · 310 g |
| Langue et grammaire | Allemand |
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