This book proposes the various types of new Ridge regression estimators to deal with the problem of multicollinearity in multiple linear regression analysis.An Ordinary ridge regression estimators and an orthonormal( ridge regression estimators have been derived by selecting the values for ridge parameter based on studentized residuals.A partitioned linear regression model has been specified and the ridge regression estimator has been developed by using Internally studentized residual sum of squares.besides these,an Adaptive General Ridge regression estimator's and a new combined restricted ridge regression estimators have been proposed along with iterative procedures for the solutions of elements of ridge parameters matrix.
| Autorius: | M. Pushpalatha, M. Bhupathi Naidu, Balasiddamuni Pagadala, |
| Leidėjas: | LAP LAMBERT Academic Publishing |
| Išleidimo metai: | 2013 |
| Knygos puslapių skaičius: | 216 |
| ISBN-10: | 3659389765 |
| ISBN-13: | 9783659389764 |
| Formatas: | 220 x 150 x 13 mm. Knyga minkštu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „Linear Regression Models under Multicollinearity: Ridge Regression Inferential Techniques“
