Comparing error estimation measures for polynomial and kriging approximation of noise-free functions

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Predictive quantification of surrogate model fidelity based on modal variations with sample density (2015, methodology): “Goel et al. (2009) and Goel and Stander (2009) compared different error measures including PRESS and MSE for Kriging, and found that PRESS provided better performance compared to the other methods, as a fidelity prediction and as a surrogate model selection criterion.”
Using Cross Validation to Design Conservative Surrogates (2010, methodology): “For unbiased surrogates, there has been research pointing to the utility of cross validation [24–29] for selecting the most accurate surrogate from several fitted surrogates.”
Recent advances in surrogate-based optimization (2009, background): “, xm}T for a one variable quadratic [27, 58].”
Review of multi-fidelity models (2016, methodology): “These methods aim to determine the coefficients of these basis functions by employing optimization techniques that minimize the discrepancy between the observed data and the predictive model [223, 79].”