A Leisurely Look at the Bootstrap, the Jackknife, and Cross-Validation
Bibliographic Data
| ID | 23322142 |
|---|---|
| Authors | Bradley Efron (Stanford University), Gail Gong (Carnegie Mellon University) |
| Year | 1983 |
| Volume | 37 |
| Issue | 1 |
| Pages | 36-48 |
| Publication date | 1983-02-01 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | The American Statistician (JOURNAL) |
| Journal identifiers | ISSN: 0003-1305 • E-ISSN: 1537-2731 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/00031305.1983.10483087 |
| OpenAlex | W1976927254 |
| Language | EN |
| Citations received | 120 |
| References cited | 12 |
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.
Econometrics · Estimator · Jackknife resampling · Mathematical proof · Nonparametric statistics · Standard error · Statistician · Statistics · Advanced Statistical Methods and Models · Computer Science · Mathematics · Statistical Methods and Bayesian Inference · Statistical Methods and Inference
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| Unique citing works | 120 |
|---|---|
| Citations per year | 2,86 |
| Citation span | 1984 - 2025 (42) |
| Citation velocity | recent |
| Highly cited | Yes |
| Citation types | Neutral: 86 |