Furthermore, by resampling residuals and randomly reattaching them to fitted values, the
procedure implicitly assumes that the errors are identically distributed. If, for example, the
true errors have nonconstant variance, then this property will not be reflected in the resampled
residuals. Likewise, the unique impact of a high-leverage outlier will be lost to the resampling.16