3 papers
stat.ME2023
A Graphical Comparison of Screening Designs using Support Recovery Probabilities
Kade Young, Maria L. Weese, Jonathan W. Stallrich +2
A screening experiment attempts to identify a subset of important effects using a relatively small number of experimental runs. Given the limited run size and a large number of pos…
stat.ME2022
D- and A-optimal Screening Designs
Jonathan Stallrich, Katherine Allen-Moyer, Bradley Jones
In practice, optimal screening designs for arbitrary run sizes are traditionally generated using the D-criterion with factor settings fixed at +/- 1, even when considering continuo…
stat.ME2018
Sequential Optimization in Locally Important Dimensions
Munir A. Winkel, Jonathan W. Stallings, Curt B. Storlie +1
Optimizing an expensive, black-box function is challenging when its input space is high-dimensional. Sequential design frameworks first model with a surrogate…