Balanced Design of Bootstrap Simulations
将Davison等人提出的自助法模拟平衡设计从一阶扩展到二阶，主要影响方差估计，并给出数值例子说明正反效果。
SUMMARY Davison et al. (1986) have shown that finite bootstrap simulations can be improved by forcing balance in the aggregate of simulated data sets. Their methods yield first-order balance, which principally affects bootstrap estimation of bias. Here we extend the methodology to second-order balance, which principally affects bootstrap estimation of variance. The particular techniques involve Latin square and balanced incomplete block designs. Numerical examples are given to illustrate both the positive and the negative features of the balanced simulations.