Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Usanifu wa Bootstrap wa Kigezo (Parametric Bootstrap)× | Bootstrap ya BCa (iliyorekebishwa kwa upendeleo na kuharakishwa)× | Utoaji wa Hitimisho kwa Njia ya Bootstrap× | |
|---|---|---|---|
| Nyanja | Takwimu | Takwimu | Takwimu |
| Familia | Regression model | Regression model | Regression model |
| Mwaka wa asili≠ | 1993 | 1987 | 1979 |
| Mwanzilishi≠ | Efron & Tibshirani; Davison & Hinkley | Bradley Efron | Bradley Efron |
| Aina≠ | Resampling-based inference (model-based) | Resampling confidence interval | Resampling-based inference |
| Chanzo asilia≠ | Efron, B. & Tibshirani, R. J. (1993). An Introduction to the Bootstrap. CRC Press. ISBN: 978-0412042317 | Efron, B. (1987). Better Bootstrap Confidence Intervals. Journal of the American Statistical Association, 82(397), 171-185. DOI ↗ | Efron, B. (1979). Bootstrap Methods: Another Look at the Jackknife. Annals of Statistics, 7(1), 1-26. DOI ↗ |
| Majina mbadala≠ | parametrik bootstrap, model-based bootstrap, parametric resampling | BCa Bootstrap (Bias-Corrected Accelerated), bias-corrected accelerated bootstrap, BCa confidence interval | bootstrap, bootstrap resampling, nonparametric bootstrap, Bootstrap Çıkarımı |
| Zinazohusiana | 5 | 5 | 5 |
| Muhtasari≠ | The parametric bootstrap is a resampling method that estimates standard errors and confidence intervals by drawing repeated samples from a parametric model that has been fitted to the data. Developed in the bootstrap literature of Efron and Tibshirani (1993) and Davison and Hinkley (1997), it replaces analytic derivations for non-normal distributions and complex statistics. | The BCa bootstrap is a resampling method, introduced by Bradley Efron in 1987, that produces more accurate confidence intervals than the plain percentile bootstrap by applying a bias correction and an acceleration adjustment. It is recommended for skewed distributions and small samples. | Bootstrap inference, introduced by Bradley Efron in 1979, estimates the sampling distribution of a statistic by repeatedly resampling the observed data with replacement. It requires no distributional assumption and produces reliable confidence intervals even in small samples. |
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