I-Optimality Algorithm and Implementation
Selden B. Crary, L.M.C. Hoo, Mark Tennenhouse · Computational Statistics · 1992
Exact designs of experiments are frequently sought that are optimal at producing predictive response-surface models. Until recently, however, there have not been any software systems capable of finding such designs on continuous spaces, except for very specific models. We present the algorithmic and implementation details of our software program, I-OPT TM [1], for finding exact, continuous-space designs that minimize the integrated expected variance of prediction over the region of interest (sometimes known as either the I- or IV-optimality criterion) for general quantic models. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.