Unbiased risk estimation and scoring rules

2011/05/11 by Ehm, Werner
#FOS: Mathematics #Statistics Theory (math.ST)

paper · doi:10.48550/arxiv.1105.2165

Abstract

Stein unbiased risk estimation is generalized twice, from the Gaussian shift model to nonparametric families of smooth densities, and from the quadratic risk to more general divergence type distances. The development relies on a connection with local proper scoring rules.

Related

• Unbiased estimation of risk
• Stein Estimation for Infinitely Divisible Laws
• Stein COnsistent Risk Estimator (SCORE) for hard thresholding
• Tractable Evaluation of Stein's Unbiased Risk Estimate with Convex Regularizers
• Second order Stein: SURE for SURE and other applications in high-dimensional inference