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Wiley InterScience | ||||||||||||||
  Journal of the Royal Statistical Society: Series C (Applied Statistics)Volume 56 Issue 3, Pages 347 - 364 Published Online: 18 May 2007 © 2010 The Royal Statistical Society and Blackwell Publishing Ltd Published on behalf of the Royal Statistical Society
Abstract | References | Full Text: HTML, PDF (Size: 522K) | Related Articles | Citation Tracking  A candidate-set-free algorithm for generating D-optimal split-plot designs 1Re-use of this article is permitted in accordance with the Creative Commons Deed, Attribution 2.5, which does not permit commercial exploitation. Copyright 2007 Royal Statistical Society KEYWORDS
D-optimality • Exchange algorithm • Hard-to-change factors • Multistratum design • Split-plot design • Tailor-made design ABSTRACTSummary. We introduce a new method for generating optimal split-plot designs. These designs are optimal in the sense that they are efficient for estimating the fixed effects of the statistical model that is appropriate given the split-plot design structure. One advantage of the method is that it does not require the prior specification of a candidate set. This makes the production of split-plot designs computationally feasible in situations where the candidate set is too large to be tractable. The method allows for flexible choice of the sample size and supports inclusion of both continuous and categorical factors. The model can be any linear regression model and may include arbitrary polynomial terms in the continuous factors and interaction terms of any order. We demonstrate the usefulness of this flexibility with a 100-run polypropylene experiment involving 11 factors where we found a design that is substantially more efficient than designs that are produced by using other approaches. [Received January 2006. Revised January 2007] | 
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 | Significance |
Try to forecast the results of 10 different events, some sporting, some cultural, some just odd, that will take place between May and July 2010. Have Fun! | |
