The jackknife: a resampling method with connections to the bootstrap

• Published in: Wiley interdisciplinary reviews. Computational statistics 2012-03, Vol.4 (2), p.224-226
• Main Author: Chernick, Michael R.
• Format: Article
• Language: English
• Subjects: bias correction; bootstrap; Confidence intervals; cross-validation; Data; Data analysis; Data processing; Graphical methods; Methods; Non-parametric methods; Permutations; pseudovalues; Resampling; Statistical analysis; Statistical methods; Statistics; Variance analysis
• ISSN: 1939-5108; 1939-0068
• DOI: 10.1002/wics.202

The jackknife is a statistical method that dates back to the late 1940s. After the introduction of the bootstrap in the late 1970s it became classified with permutation methods, bootstrap and subsampling as a resampling method. In the beginning the jackknife was used for bias correction and variance estimation. As time went on it was generalized and used more widely including its use in generating approximate confidence intervals for statistical parameters. This article provides an overview of the jackknife along with its connections to the bootstrap and the other resampling methods. Key research articles and books related to the jackknife and the bootstrap are noted. WIREs Comput Stat 2012, 4:224–226. doi: 10.1002/wics.202 This article is categorized under: Statistical and Graphical Methods of Data Analysis > Bootstrap and Resampling Statistical and Graphical Methods of Data Analysis > Nonparametric Methods Statistical and Graphical Methods of Data Analysis > Robust Methods