Statistics Nonparametric inference Concept
Bootstrap
Summary
The bootstrap estimates the sampling distribution of a statistic by resampling the observed data with replacement. It treats the empirical distribution function of the sample as if it were the unknown true distribution. It then recomputes the statistic on many simulated samples drawn from it. From these replicates one gets standard errors, bias estimates and confidence intervals without explicit formulas. Bradley Efron introduced it in 1979, and it is one of the most used tools of modern statistics.
Further reading
About this page
| Tag | 40ATJEVR32 |
|---|---|
| URI | m2://40ATJEVR32 |
| Kind | concept |
| Writing | W0 stub |
| MSC | 62G09, 62F40 |
| Same as |
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