The V-fold jackknife for semiparametric inference: variance estimation, confidence intervals, and simultaneous confidence bands
This work develops the V-fold jackknife as a computationally efficient and theoretically justified alternative for semiparametric inference and extends the theory to generalized asymptotically linear estimators with diverging influence-function variance and slower-than-\sqrt n convergence.