Quasi-regression with shrinkage

Quasi-regression is a method of Monte Carlo approximation useful for global sensitivity analysis. This paper presents a new version, incorporating shrinkage parameters of the type used in wavelet approximation. As an example application, a black box function from machine learning is analyzed. That function is nearly a sum of functions of one and two variables and the first variable acting alone accounts for more than half of the variance.

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