Estimating distribution sensitivity using generalized likelihood ratio method

Abstract

We propose a generalized likelihood ratio estimator for the distribution sensitivity in a general framework. Applications on quantile sensitivity, sensitivity of distortion risk measure, and gradient-based maximum likelihood estimation are put together under a single umbrella, and addressed uniformly by the proposed estimator. Numerical experiments substantiate the efficiency of the new method.