Introduction to the Non-Parametric Bootstrap

Berrar, Daniel (2019). Introduction to the Non-Parametric Bootstrap. In: Ranganathan, Shoba; Gribskov, Michael; Nakai, Kenta; Schönbach, Christian and Cannataro, Mario eds. Encyclopedia of Bioinformatics and Computational Biology. Reference Module in Life Sciences, 1. Elsevier, pp. 766–773.

DOI: https://doi.org/10.1016/B978-0-12-809633-8.20350-6

Abstract

The bootstrap is a computation-intensive data resampling methodology for assessing the accuracy of a statistical estimator and for making inferences about unknown population parameters. This article provides an introduction to the ordinary non-parametric bootstrap, with a focus on two applications that are of particular relevance to bioinformatics: Bootstrap confidence intervals and bootstrap error estimates of predictive performance.

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