Consistency of the Generalized Bootstrap for Degenerate $U$-Statistics

By Marie Husková, P. Janssen. 1993

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

A Kernelized Stein Discrepancy for Goodness-of-fit Tests (2016, methodology): “In this work, we adopt the bootstrap method suggested in Huskova & Janssen (1993); Arcones & Gine (1992): We repeatedly draw multinomial random weights ( w 1 , . . . w n ) ∼ Mult( n ; 1 n , . . . , 1 n ) , and calculate boot-strap sample and then calculate the empirical quantile ˆ γ 1 − α of n ˆ S…”
Gaussian and bootstrap approximations for high-dimensional U-statistics and their applications (2016, methodology): “For univariate U-statistics, the empirical bootstrap was studied in [7, 2] and the randomly reweighted bootstrap of the form (15) was proposed in [42, 40], where a different class of random weights wi was considered satisfying wi = ξi/(n −1∑n i=1 ξi) such that ξi are iid non-negative random variable”