Title 



An algorithm for finding Defficient equivalentestimation secondorder splitplot designs
 
Author 



 
Abstract 



Many industrial experiments involve restricted rather than complete randomization. This often leads to the use of splitplot designs, which limit the number of independent settings of some of the experimental factors. These factors, named wholeplot factors, are often, in some way, hard to change. The remaining factors, called subplot factors, are easier to change. Their levels are therefore independently reset for every run of the experiment. In general, model estimation from data from splitplot experiments requires the use of generalized least squares (GLS). However, for some splitplot designs, the ordinary least squares (OLS) estimator will produce the same factoreffect estimates as the GLS estimator. These designs are called equivalentestimation splitplot designs and offer the advantage that estimation of the factor effects does not require estimation of the variance components in the splitplot model. While many of the equivalentestimation secondorder responsesurface designs presented in the literature do not perform well in terms of estimation efficiency (as measured by the Doptimality criterion), Macharia and Goos (2010) showed that, in many instances, it is possible to generate secondorder equivalentestimation splitplot designs that are highly efficient and, hence, provide precise factoreffect estimates. In this work, we present an algorithm that allows us to (i) identify equivalentestimation designs for scenarios where Macharia and Goos (2010) did not find equivalentestimation designs and (ii) find equivalentestimation designs that outperform those of Macharia and Goos (2010) in terms of the Doptimality criterion. We also study the performance of equivalentestimation designs when it comes to estimating the variance components in the splitplot model and observe that they outperform Doptimal designs in this respect.   
Language 



English
 
Source (journal) 



Journal of quality technology.  Milwaukee, Wis.  
Publication 



Milwaukee, Wis. : 2012
 
ISSN 



00224065
 
Volume/pages 



44:4(2012), p. 363374
 
ISI 



000309085000005
 
