Target output distribution and distribution of bias for statistical model validation given a limited number of test data

Abstract

Simulation model must be validated with experimental data to correctly predict the outputs of engineered systems before they can be used with confidence. While doing so, pointwise comparison between predicted output by simulation model and experimental data for model verification and validation (VV (2) the reallocated test dataset by a quality checking process and balance sampling leads to better matching to the true output distribution; and (3) the distribution of bias is effectively used to understand the model’s accuracy and model confidence for comparison study.