Details

Autor(en) / Beteiligte

• Wang, Chunyan
• Mee, Robert W.

Titel

Saturated and supersaturated order-of-addition designs

Ist Teil von

• Journal of statistical planning and inference, 2022-07, Vol.219, p.204-215

Ort / Verlag

Elsevier B.V

Erscheinungsjahr

2022

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Van Nostrand’s pairwise order model has been the most popular model for analyzing order-of-addition experiments. Here we construct designs of minimal size for the pairwise order model, considering both D-optimality, as well as the prediction-based I- and G-optimality criteria. Even these saturated designs grow large when the number of components exceeds 10. Thus, we also propose Bayesian D-optimal designs, which may have fewer runs than the number of parameters for the pairwise order model. These supersaturated designs may be used as screening designs for applications where the number of components is large. •We generate improved minimal saturated designs for the pairwise order (PWO) model.•We offer G- and I-optimal designs, which emphasize prediction rather than parameter estimation.•We propose Bayesian D-optimal order of addition designs when the number of components is large.•We provide code for generating saturated (and larger) designs.