Quasi-regression with shrinkage

  • Authors:
  • Tao Jiang;Art B. Owen

  • Affiliations:
  • Department of Statistics, Stanford University, Stanford, CA;Department of Statistics, Stanford University, Stanford, CA

  • Venue:
  • Mathematics and Computers in Simulation - Special issue: 3rd IMACS seminar on Monte Carlo methods - MCM 2001
  • Year:
  • 2003

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Abstract

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.