A note on Wild and Pignatiello's experimental design strategy

SIMULATION ◽  
1992 ◽  
Vol 58 (6) ◽  
pp. 393-394
Author(s):  
Jack P. C. Kleijnen
2021 ◽  
Vol 1 (1) ◽  
pp. 49-58
Author(s):  
Mårten Schultzberg ◽  
Per Johansson

AbstractRecently a computational-based experimental design strategy called rerandomization has been proposed as an alternative or complement to traditional blocked designs. The idea of rerandomization is to remove, from consideration, those allocations with large imbalances in observed covariates according to a balance criterion, and then randomize within the set of acceptable allocations. Based on the Mahalanobis distance criterion for balancing the covariates, we show that asymptotic inference to the population, from which the units in the sample are randomly drawn, is possible using only the set of best, or ‘optimal’, allocations. Finally, we show that for the optimal and near optimal designs, the quite complex asymptotic sampling distribution derived by Li et al. (2018), is well approximated by a normal distribution.


1998 ◽  
Vol 31 (8) ◽  
pp. 73-78 ◽  
Author(s):  
R. Takors ◽  
D. Weuster-Botz ◽  
W. Wiechert ◽  
C. Wandrey

AIChE Journal ◽  
2005 ◽  
Vol 51 (6) ◽  
pp. 1773-1781 ◽  
Author(s):  
Sébastien Issanchou ◽  
Patrick Cognet ◽  
Michel Cabassud

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