On Sample Reuse Methods for Dependent Data

Abstract

SUMMARYWe suggest a sample reuse method for dependent data, based on a cross between the block bootstrap and Richardson extrapolation. Instead of simulating a same size resample by resampling blocks and placing them end to end, it analyses the blocks directly and employs a variant of Richardson extrapolation to adjust for block size. A simple empirical rule, also based on Richardson extrapolation, is suggested for empirically selecting the block size. Performance in the contexts of distribution and bias estimation is discussed via theoretical analysis and numerical simulation.