Calculating quantiles of noisy distribution functions using local linear regressions

A novel, practical approach for calculation of quantiles from noisy distribution functions is presented. The algorithm is based on recursive local linear regressions on the probit scale. It is compared to the Robbins–Monro approach for stochastic root finding and two deterministic root finding methods on a number of practically relevant examples, including an application to the mvtnorm R package.