Bayesian methodsBayesian / computational
缺失数据时的自助法模拟
缺失数据时的自助法模拟将基于重采样的方差估计与对不完整观测值的原则性处理相结合。该方法不删除个案或假设数据完整，而是在自助法循环中直接整合插补或加权，将因缺失带来的额外不确定性传播到最终的标准误差和置信区间。
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来源
- Efron, B. & Tibshirani, R. J. (1993). An Introduction to the Bootstrap. Chapman and Hall/CRC. ISBN: 978-0412042317
- Little, R. J. A. & Rubin, D. B. (2019). Statistical Analysis with Missing Data (3rd ed.). Wiley. ISBN: 978-0470526798
如何引用本页
ScholarGate. (2026, June 3). Bootstrap Simulation with Missing Data Handling. ScholarGate. https://scholargate.app/zh/bayesian/bootstrap-simulation-with-missing-data
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.
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- Multiple Imputation统计学↔ compare
- 缺失数据的序贯蒙特卡洛方法贝叶斯↔ compare