Abstract
Stein and Haff's technique is used to obtain improved estimators of the multinormal precision matrix under a loss introduced by Efron and Morris (1976). The technique is to obtain solutions to a certain differential inequality involving the eigenvalues of the sample covariance matrix. A new class of improved estimators are obtained by solving the differential inequality.
| Original language | English |
|---|---|
| Pages (from-to) | 141-152 |
| Number of pages | 12 |
| Journal | Statistics and Risk Modeling |
| Volume | 8 |
| Issue number | 2 |
| DOIs | |
| State | Published - Feb 1990 |
Bibliographical note
Funding Information:by AF0SR Grant Number 89-0225 supported by the NSF Grant Number by NSF EPSC0R Grant, RI1-8610671
Funding
by AF0SR Grant Number 89-0225 supported by the NSF Grant Number by NSF EPSC0R Grant, RI1-8610671
| Funders | Funder number |
|---|---|
| NSF EPSC0R | RI1-8610671 |
| National Science Foundation (NSF) |
Keywords
- Wishart distribution
- empirical Bayes estimators
- matrix means
- minimax estimators
- precision matrix
ASJC Scopus subject areas
- Statistics and Probability
- Modeling and Simulation
- Statistics, Probability and Uncertainty