Space-Filling Designs

How many success-or-failure observations should we collect from a computer simulation? Often, researchers use space-filling design of experiments when planning modeling and simulation (M&S) studies. We are not satisfied with existing guidance on justifying the number of runs when developing these designs, either because the guidance is insufficiently justified, does not provide an unambiguous answer, or is not based on optimizing a statistical measure of merit. Analysts should use confidence interval margin of error as the statistical measure of merit for M&S studies intended to characterize overall M&S behavioral trends....

This document presents arguments and methods for using space-filling designs (SFDs) to plan modeling and simulation (M&S) data collection. Suggested Citation Avery, Kelly, John T Haman, Thomas Johnson, Curtis Miller, Dhruv Patel, and Han Yi. Test Design Challenges in Defense Testing. IDA Product ID 3002855. Alexandria, VA: Institute for Defense Analyses, 2024. Slides: Paper:

Space-Filling Designs are a common choice of experimental design strategy for computer experiments. This paper compares space filling design types based on their theoretical prediction variance properties with respect to the Gaussian Process model. Suggested Citation Silvestrini, Rachel T., Douglas C. Montgomery, and Bradley Jones. “Comparing Computer Experiments for the Gaussian Process Model Using Integrated Prediction Variance.” Quality Engineering 25, no. 2 (April 2013): 164–74. https://doi.org/10.1080/08982112.2012.758284. Paper: