An improved confidence ellipsoid for the linear regression model
- 1 May 1990
- journal article
- research article
- Published by Taylor & Francis in Journal of Statistical Computation and Simulation
- Vol. 36 (1) , 9-18
- https://doi.org/10.1080/00949659008811249
Abstract
In a Monte Carlo experiment, we explore the coverage probability and volume of a percentile bootstrap confidence ellipsoid centered at the Stein-rule estimator of a multivariate normal mean. The ellipsoid we consider corresponds to the “improved-F” studied by Ullah, Carter, and Srivastava (1984, 1989) who have derived the small sigma and large-T asymptotic expansions of its distribution and studied the resulting approximations in a Monte Carlo setting. Unlike the Ullah et al. ellipsoid, the bootstrap ellipsoid covers the parameter point at or above nominal levels over large regions of the parameter space.Keywords
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