Bootstrap Methods¶
Efron, B. (1979). Bootstrap Methods: Another Look at the Jackknife. The Annals of Statistics, 7(1), 1-26.
Cited by¶
6 citations across 6 artifacts.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Bayesian Updating
This sourceEfron bootstrap computational inference method as nonparametric alternative to parametric Bayesian posteriors.
- Bootstrapping
- Entrepreneurship and finance: bootstrapped startups growing from revenue rather than external capital, founder savings funding an initial product, and revenue reinvestment compounding growth without dilution. Statistics and machine learning: the nonparametric bootstrap (resampling the sample to estimate variability without a larger study), bagging, and bootstrap confidence intervals and hypothesis tests.
This sourceIntroduces the nonparametric bootstrap: treat the observed sample as the population and resample from it with replacement to estimate sampling variability without an external replication study — the name-giving self-construction-from-a-seed method.
Supported in partVerified against the publisher's abstract
Efron's abstract introduces the bootstrap for estimating a statistic's sampling distribution from the observed sample, backing only the nonparametric-bootstrap clause of this claim.
“A general method, called the "bootstrap," is introduced, and shown to work satisfactorily on a variety of estimation problems.”
- Entrepreneurship and finance: bootstrapped startups growing from revenue rather than external capital, founder savings funding an initial product, and revenue reinvestment compounding growth without dilution. Statistics and machine learning: the nonparametric bootstrap (resampling the sample to estimate variability without a larger study), bagging, and bootstrap confidence intervals and hypothesis tests.
- Nonparametric Methods
- The resampling-based variance estimation
This sourceEfron bootstrap computational inference method as nonparametric alternative to parametric Bayesian posteriors.
Supported in partVerified against the publisher's abstract
Efron's abstract introduces the bootstrap and lists variance of the sample median among its worked examples of estimation from the observed data.
“variance of the sample median, error rates in a linear discriminant analysis”
- The resampling-based variance estimation
- Sampling (Representativeness)
This sourceEfron bootstrap computational inference method as nonparametric alternative to parametric Bayesian posteriors.
Mechanisms¶
- Bootstrap-Like Checks
- Bradley Efron's bootstrap generalized this into one of the most widely used tools in applied statistics precisely because it asks so little about the distribution's form.
This sourceIntroduces a resampling method for estimating sampling distributions from data drawn from an unknown distribution.
- Bradley Efron's bootstrap generalized this into one of the most widely used tools in applied statistics precisely because it asks so little about the distribution's form.
- Resampling Robustness Audit
- Its strength is exposing false precision from small or influential samples, cheaply and without new data: the bootstrap approximates the sampling distribution of almost any statistic by resampling the data, so instability that a formula-based standard error would paper over becomes visible.
This sourceIntroduces the bootstrap as estimating a statistic’s sampling distribution by repeatedly resampling the observed data.
- Its strength is exposing false precision from small or influential samples, cheaply and without new data: the bootstrap approximates the sampling distribution of almost any statistic by resampling the data, so instability that a formula-based standard error would paper over becomes visible.
Verification¶
Does it exist? Confirmed. This work's DOI resolves to a registered record, which fixes its identity. That is all it fixes.
Does it back the claim? Read against the text for 2 of 6 citations: 2 supported in part. Each verdict is shown under its citation below, with what in the work backs the sentence.
Was it audited? Yes. A second, independent pass read the citation against the article text and recorded a verdict.
Support is checked per citation rather than per work — the same source can be cited soundly in one article and wrongly in another. Per-citation recording began recently, so a citation with no recorded check is a gap in the record rather than evidence it went unchecked.
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Registry ID ref:f28273444cd7 · see in the full table