LOCAL VORONOI TESSELLATIONS FOR ROBUST MULTIWAVE CALIBRATION OF COMPUTER MODELS

History matching using Gaussian process emulators is a well-known methodology for the calibration of computer models. It attempts to identify the parts of input parameter space that are likely to result in mismatches between simulator outputs and physical observations by using emulators. These parts are then ruled out. The remaining "not ruled out yet" (NROY) input space is then searched for good matches by repeating the history matching process. An easily neglected limitation of this method is that the emulator must simulate the target NROY space well, else good parameter choices can be ruled out. We show that even when an emulator passes standard diagnostic checks on the whole parameter space, good parameter choices can easily be ruled out. We present novel methods for detecting these cases and a Local Voronoi Tessellation method for a robust approach to calibration that ensures that the true NROY space is retained and parameter inference is not biased.