Abstract #300016

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JSM 2003 Abstract #300016
Activity Number: 294
Type: Contributed
Date/Time: Tuesday, August 5, 2003 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistical Computing
Abstract - #300016
Title: Multistep Sequential and Accelerated Sequential Procedures for a Replicable Linear Model
Author(s): Greg Cicconetti*+ and Nitis Mukhopadhyay and Mun S. Son and Yong-Cheol Ko
Companies: Muhlenberg College and University of Connecticut and University of Vermont and University of Vermont
Address: Dept. of Math Sciences, Allentown, PA, 18104,
Keywords: ellipsoidal confidence regions ; fixed-maximum diameter ; multi-step acceleration
Abstract:

Chatterjee (1990) gave a multistep sequential methodology to construct a fixed-size confidence region for the mean of a replicable linear model. This methodology used the largest characteristic root of an appropriate conditional dispersion matrix. We propose new multistep sequential and accelerated sequential methodologies which are more efficient in lowering the "oversampling" rate substantially. Accelerated versions of these estimation techniques further reduce sampling operations and these preserve crucial properties associated with the original methodologies of Chatterjee (1990). A substantial part of this investigation includes a thorough comparison of all available methodologies for moderate sample sizes. Some limited robustness issues are addressed.

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