Efficiency bounds for product designs in linear models

Rainer Schwabe; Weng Kee Wong

doi:10.1023/A:1004087314831

Efficiency bounds for product designs in linear models

Rainer Schwabe
, Weng Kee Wong

Department of Statistics

Research output: Contribution to journal › Article › peer-review

Abstract

We provide lower efficiency bounds for the best product design for an additive multifactor linear model. The A-optimality criterion is used to demonstrate that our bounds are better than the conventional bounds. Applications to other criteria, such as IMSE (integrated mean squared error) criterion are also indicated. In all the cases, the best product design appears to perform better when there are more levels in each factor but decreases when more factors are included. Explicit efficiency formulas for non-additive models are also constructed.

Original language	English
Pages (from-to)	723-730
Number of pages	8
Journal	Annals of the Institute of Statistical Mathematics
Volume	51
Issue number	4
DOIs	https://doi.org/10.1023/A:1004087314831
Publication status	Published - 1999

All Science Journal Classification (ASJC) codes

Statistics and Probability

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10.1023/A:1004087314831

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abstract = "We provide lower efficiency bounds for the best product design for an additive multifactor linear model. The A-optimality criterion is used to demonstrate that our bounds are better than the conventional bounds. Applications to other criteria, such as IMSE (integrated mean squared error) criterion are also indicated. In all the cases, the best product design appears to perform better when there are more levels in each factor but decreases when more factors are included. Explicit efficiency formulas for non-additive models are also constructed.",

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AB - We provide lower efficiency bounds for the best product design for an additive multifactor linear model. The A-optimality criterion is used to demonstrate that our bounds are better than the conventional bounds. Applications to other criteria, such as IMSE (integrated mean squared error) criterion are also indicated. In all the cases, the best product design appears to perform better when there are more levels in each factor but decreases when more factors are included. Explicit efficiency formulas for non-additive models are also constructed.

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JO - Annals of the Institute of Statistical Mathematics

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Efficiency bounds for product designs in linear models

Abstract

All Science Journal Classification (ASJC) codes

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