ABSTRACT
The bootstrap was introduced in 1979 by B. Efron, with further developments in 1981, 1982, and numerous other publications including the monograph of Efron and R. Tibshirani. M. A. Chernick has an extensive bibliography. A. Davison and D. Hinkley is a comprehensive reference with many applications. Bootstrap methods are a class of nonparametric Monte Carlo methods that estimate the distribution of a population by resampling. Resampling methods treat an observed sample as a finite population, and random samples are generated from it to estimate population characteristics and make inferences about the sampled population. The jackknife is another resampling method, proposed by Quenouille for estimating bias, and by J. Tukey for estimating standard error, a few decades earlier than the bootstrap. Efron is a good introduction to the jackknife. A bootstrap percentile interval uses the empirical distribution of the bootstrap replicates as the reference distribution.
