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.
CITATION STYLE
Young, G. A., Shao, J., & Tu, D. (1996). The Jackknife and Bootstrap. Journal of the Royal Statistical Society. Series A (Statistics in Society), 159(3), 631. https://doi.org/10.2307/2983351
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