Efficient resampling methods for nonsmooth estimating functions

We propose a simple and general resampling strategy to estimatevariances for parameter estimators derived from nonsmooth estimatingfunctions. This approach applies to a wide variety of semiparametricand nonparametric problems in biostatistics. It does not requiresolving estimating equations and is thus much faster than theexisting resampling procedures. Its usefulness is illustratedwith heteroscedastic quantile regression and censored data rankregression. Numerical results based on simulated and real dataare provided.