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A Leisurely Look at the Bootstrap, the Jackknife, and Cross-Validation
Bradley Efron and Gail Gong
The American Statistician
Vol. 37, No. 1 (Feb., 1983), pp. 36-48
Stable URL: http://www.jstor.org/stable/2685844
Page Count: 13
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This is an invited expository article for The American Statistician. It reviews the nonparametric estimation of statistical error, mainly the bias and standard error of an estimator, or the error rate of a prediction rule. The presentation is written at a relaxed mathematical level, omitting most proofs, regularity conditions, and technical details.
The American Statistician © 1983 American Statistical Association