Blocking response surface designs

The design of experiments involving more than one blocking factor and quantitative explanatory variables is discussed, the focus being on two key aspects of blocked response surface designs: optimality and orthogonality. First, conditions for orthogonally blocked experiments are derived. Next, an al...

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Bibliographic Details
Published inComputational statistics & data analysis Vol. 51; no. 2; pp. 1075 - 1088
Main Authors Goos, P., Donev, A.N.
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier B.V 15.11.2006
Elsevier Science
Elsevier
SeriesComputational Statistics & Data Analysis
Subjects
D-optimality
Exact sciences and technology
Exchange algorithm
Experimental design
Fixed blocks
General topics
Mathematics
Multivariate analysis
Numerical analysis
Numerical analysis. Scientific computation
Numerical methods in probability and statistics
Orthogonality
Probability and statistics
Random blocks
Sciences and techniques of general use
Statistics
D-optimality
Fixed blocks
Random blocks
Orthogonality
Exchange algorithm
Data analysis
Algorithmics
Optimal D design
Statistical computation
Block design
Experimental design
Response surface
Optimal design(statistics)
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Summary:The design of experiments involving more than one blocking factor and quantitative explanatory variables is discussed, the focus being on two key aspects of blocked response surface designs: optimality and orthogonality. First, conditions for orthogonally blocked experiments are derived. Next, an algorithmic approach to compute D-optimal designs is presented. Finally, the relationships between design optimality and orthogonality in the context of response surface experiments are discussed in detail.
ISSN:0167-9473
1872-7352
DOI:10.1016/j.csda.2005.11.003