A Score Based Approach to Wild Bootstrap Inference

  title={A Score Based Approach to Wild Bootstrap Inference},
  author={Patrick Kline and Andr{\'e}s Santos},
We propose a generalization of the wild bootstrap of Wu (1986) and Liu (1988) based upon perturbing the scores of M-estimators. This “score bootstrap” procedure avoids recomputing the estimator in each bootstrap iteration, making it substantially less costly to compute than the conventional nonparametric bootstrap, particularly in complex nonlinear models. Despite this computational advantage, in the linear model, the score bootstrap studentized test statistic is equivalent to that of the… CONTINUE READING


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