Regression model
参数自举法
参数自举法是一种重采样方法，它通过从已拟合到数据上的参数模型中反复抽取样本来估计标准误差和置信区间。该方法由 Efron 和 Tibshirani (1993) 以及 Davison 和 Hinkley (1997) 在自举法文献中提出，它取代了针对非正态分布和复杂统计量的解析推导。
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Method map
The neighbourhood of related methods — select a node to explore.
来源
- Efron, B. & Tibshirani, R. J. (1993). An Introduction to the Bootstrap. CRC Press. ISBN: 978-0412042317
- Davison, A. C. & Hinkley, D. V. (1997). Bootstrap Methods and Their Application. Cambridge University Press. ISBN: 978-0521574716
如何引用本页
ScholarGate. (2026, June 1). Parametric Bootstrap Resampling. ScholarGate. https://scholargate.app/zh/statistics/parametric-bootstrap
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- 贝叶斯自助法（Bayesian Bootstrap，由 Rubin 提出）统计学↔ compare
- BCa Bootstrap（偏差校正和加速法）统计学↔ compare
- Bootstrap Inference统计学↔ compare
- 置换 (随机化) 检验统计学↔ compare
- Wild Bootstrap for Regression Inference统计学↔ compare