Least squares, preliminary test and Stein-type estimation in general vector AR(p) models |
| |
Authors: | S. E. Ahmed,& A. K. Basu |
| |
Affiliation: | Department of Mathematics and Statistics, University of Regina, Regina, Saskatchewan, Canada,;Department of Statistics, University of Calcutta, Calcutta, India |
| |
Abstract: | In the general vector autoregressive process AR ( p ), multivariate least square estimation (LSE)/maximum likelihood estimation (MLE) of a subset of the parameters is considered when the complementary subset is suspected to be redundant. This may be viewed as a special case of linear constraints of autoregressive parameters. We incorporate this nonsample information in the estimation process and propose preliminary test and Stein-type estimators for the target subset of parameters. Under local alternatives their asymptotic properties are investigated and compared with those of unrestricted and restricted LSE. The dominance picture of the estimators is presented. |
| |
Keywords: | vector autoregressive multivariate least squares estimators asymptotic bias asymptotic distributional risk shrinkage estimators preliminary test estimators local alternatives |
|
|