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Bootstrapping

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Edited by: Published: 2010
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The bootstrap is a computer-based statistical technique that is used to obtain measures of precision of parameter estimates. Although the technique is sufficiently general to be used in time-series analysis, permutation tests, cross-validation, nonlinear regression, and cluster analysis, its most common use is to compute standard errors and confidence intervals. Introduced by Bradley Efron in 1979, the procedure itself belongs in a broader class of estimators that use sampling techniques to create empirical distributions by resampling from the original data set. The goal of the procedure is to produce analytic expressions for estimators that are difficult to calculate mathematically. The name itself derives from the popular story in which Baron von Munchausen (after whom Munchausen syndrome is also named) was stuck at the bottom of ...

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