[Jackknife and bootstrap].
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TL;DR
The jackknife and the bootstrap are two non parametric methods which provide estimates- of the bias and the variance of an estimator, without any assumption about its statistical distribution.
Abstract
The jackknife and the bootstrap are two non parametric methods which provide estimates- of the bias and the variance of an estimator, without any assumption about its statistical distribution. The jackknife is based on the observation of the estimator for subsamples, generally of size n-1, obtained from the original sample. The bootstrap is based on the observation of the estimator on size n samples drawn from the original sample. The two methods are presented, their principle is illustrated through their application to simple examples and to more complex epidemiological problems.