๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

On improved interval estimation for the generalized variance

โœ Scribed by George Iliopoulos; Stavros Kourouklis

Publisher
Elsevier Science
Year
1998
Tongue
English
Weight
703 KB
Volume
66
Category
Article
ISSN
0378-3758

No coin nor oath required. For personal study only.

โœฆ Synopsis

A confidence interval for the generalized variance of a matrix normal distribution with unknown mean is constructed which improves on the usual minimum size (i.e., minimum length or minimum ratio of endpoints) interval based on the sample generalized variance alone in terms of both coverage probability and size. The method is similar to the univariate case treated by Goutis and Casella (Ann. Statist. 19

๐Ÿ“œ SIMILAR VOLUMES

Stein-type improvements of confidence in
Stein-type improvements of confidence intervals for the generalized variance
โœ Sanat K. Sarkar ๐Ÿ“‚ Article ๐Ÿ“… 1991 ๐Ÿ› Springer Japan ๐ŸŒ English โš– 322 KB

Based on independent random matices X: p x m and S: p x p distributed, respectively, as Npm(#, E ยฎ I,~) and Wp(n, ~) with # unknown and n > p, the problem of obtaining confidence interval for IEI is considered. Stein's idea of improving the best affine equivariant point estimator of IE[ has been ada

Improved confidence estimators for the u
Improved confidence estimators for the usual one-sided confidence intervals for the ratio of two normal variances
โœ Hsiuying Wang ๐Ÿ“‚ Article ๐Ÿ“… 2002 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 116 KB

The usual conรฟdence intervals for the ratio of two normal variances are constructed from F-distribution. These conรฟdence intervals are especially important in the variance component model. In this paper, I focus on conรฟdence estimate and conditional performance of these conรฟdence intervals. Under so

Optimal variance estimation for generali
Optimal variance estimation for generalized regression predictor
โœ Arijit Chaudhuri; Debesh Roy ๐Ÿ“‚ Article ๐Ÿ“… 1997 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 760 KB

The generalized regression (greg) predictor for the finite population total of a real variable is often employed when values of an auxiliary variable are available. Several variance estimators for it do well in large samples though bearing no optimality properties. We find a variance estimator which

Improving on the Best Affine Equivariant
Improving on the Best Affine Equivariant Estimator of the Ratio of Generalized Variances
โœ George Iliopoulos; Stavros Kourouklis ๐Ÿ“‚ Article ๐Ÿ“… 1999 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 152 KB

We consider the problem of decision-theoretic estimation of the ratio of generalized variances of two matrix normal distributions with unknown means under a general loss function. The inadmissibility of the best affine equivariant estimator is established by exhibiting various improved estimators. I