Modelling by supersaturated designs

The analysis of supersaturated designs is an interesting problem of great importance since it provides economic estimates. Moreover, this problem is challenging due to the fact that the design matrix has a complicated structure. The identification of the active factors in supersaturated designs is i...

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Bibliographic Details
Published in:Computational statistics & data analysis 2008-12, Vol.53 (2), p.428-435
Main Author: Georgiou, Stelios D.
Format: Article
Language:English
Subjects:
Exact sciences and technology
Experimental design
General topics
Mathematics
Multivariate analysis
Numerical analysis
Numerical analysis. Scientific computation
Numerical methods in probability and statistics
Probability and statistics
Sciences and techniques of general use
Statistics
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Summary:The analysis of supersaturated designs is an interesting problem of great importance since it provides economic estimates. Moreover, this problem is challenging due to the fact that the design matrix has a complicated structure. The identification of the active factors in supersaturated designs is investigated. The singular value decomposition (SVD), principal components analysis and regression analysis are used together in an SVD principal regression method to reveal the hidden true linear model. Special cases are studied by using simulation data under idealized conditions. Simulations are used to investigate the performance of the method and also to compare the proposed method with other known methods from the literature.
ISSN:0167-9473
1872-7352
DOI:10.1016/j.csda.2008.08.015