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Details van artikel 3 van 16 gevonden artikelen
| Titel: |
Bootstrapping by monte carlo versus approximating the estimator and bootstrapping exactly: Cost and performance |
| Auteur: |
Oldford, R. Wayne |
| Verschenen in: |
Communications in statistics |
| Paginering: | Jaargang 14 (1985) nr. 2 pagina's 395-424 |
| Jaar: |
1985 |
| Inhoud: |
Approximations to the bootstrap estimate of bias and variance may be obtained by replacing the estimate [image omitted] to be bootstrapped by one which is linear, or [image omitted] ,or quadratic,[image omitted] , in the resampling vector p. The bootstrap bias and variance of [image omitted] and [image omitted] may then be evaluated analytically. These estimators are discussed and then investigated via a Monte Carlo experiment when [image omitted] is the least squares regression coefficient estimate. Included amongst these bias and variance estimates are the standard jackknife, Jaeckel's [1972] infinitesimal jackknife, and Hinkley's [1977] jackknife. Good performers included a quadratic infinitesimal jackknife and the Monte Carlo evaluated bootstrap when the number of replicates was about 6 or 7 times the sample size. Poor performers included the standard jackknife and Hinkley's. Further, when computational costs were held equal, bootstrapping by Monte Carlo did better than the jackknife. |
| Uitgever: |
Taylor & Francis |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
Details van artikel 3 van 16 gevonden artikelen
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