Model Discrimination Criteria on Model-Robust Designs

Recently, interest about model discrimination has been focused on methods based on model estimation. Due to the problem of model aliasing, several criteria have been proposed aimed at assessing the capacity of a design for model discrimination. Three of these measures, along with a new criterion tha...

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Bibliographic Details
Published in:	Communications in statistics. Simulation and computation Vol. 43; no. 7; pp. 1575 - 1582
Main Authors:	Androulakis, E., Angelopoulos, P., Koukouvinos, C.
Format:	Journal Article
Language:	English
Published:	Philadelphia Taylor & Francis Group 01-01-2014 Taylor & Francis Ltd
Subjects:	Aliasing AMS Subject Classification: Primary 62K15 Discrimination Discrimination criteria Non-isomorphic Orthogonal arrays Secondary 05B15 Three-level designs
Online Access:	Get full text
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Summary:	Recently, interest about model discrimination has been focused on methods based on model estimation. Due to the problem of model aliasing, several criteria have been proposed aimed at assessing the capacity of a design for model discrimination. Three of these measures, along with a new criterion that combines them and assesses the overall discrimination capacity of a design, are implemented to evaluate a class of 27-run orthogonal arrays in three levels.
Bibliography:	ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23
ISSN:	0361-0918 1532-4141
DOI:	10.1080/03610918.2012.736580