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| Bootstrap tham số× | BCa Bootstrap (Hiệu chỉnh thiên vị và Tăng tốc)× | Kiểm định hoán vị (Ngẫu nhiên hóa)× | |
|---|---|---|---|
| Lĩnh vực | Thống kê | Thống kê | Thống kê |
| Họ | Regression model | Regression model | Regression model |
| Năm ra đời≠ | 1993 | 1987 | 2005 |
| Người khởi xướng≠ | Efron & Tibshirani; Davison & Hinkley | Bradley Efron | Good (2005); Edgington & Onghena (2007); resampling tradition |
| Loại≠ | Resampling-based inference (model-based) | Resampling confidence interval | Nonparametric resampling test |
| Công trình gốc≠ | 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 ↗ | Good, P. (2005). Permutation, Parametric and Bootstrap Tests of Hypotheses (3rd ed.). Springer. ISBN: 978-0387202792 |
| Tên gọi khác≠ | parametrik bootstrap, model-based bootstrap, parametric resampling | BCa Bootstrap (Bias-Corrected Accelerated), bias-corrected accelerated bootstrap, BCa confidence interval | randomization test, exact permutation test, re-randomization test, Permütasyon Testi |
| Liên quan | 5 | 5 | 5 |
| Tóm tắt≠ | 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. | The permutation test is a nonparametric resampling procedure that builds the sampling distribution of a test statistic directly from the data by repeatedly shuffling the group labels. Developed in the resampling tradition and treated systematically by Good (2005) and Edgington & Onghena (2007), it requires no parametric distributional assumption and yields an exact p-value. |
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