So sánh phương pháp

	Suy luận Bootstrap	Phương pháp lấy mẫu lại Jackknife	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	1979	1956	2005
Người khởi xướng	Bradley Efron	Quenouille (1956); reviewed by Miller (1974)	Good (2005); Edgington & Onghena (2007); resampling tradition
Loại	Resampling-based inference	Resampling / bias and variance estimation	Nonparametric resampling test
Công trình gốc	Efron, B. (1979). Bootstrap Methods: Another Look at the Jackknife. Annals of Statistics, 7(1), 1-26.	Quenouille, M. H. (1956). Notes on Bias in Estimation. Biometrika, 43(3/4), 353-360.	Good, P. (2005). Permutation, Parametric and Bootstrap Tests of Hypotheses (3rd ed.). Springer. ISBN: 978-0387202792
Tên gọi khác	bootstrap, bootstrap resampling, nonparametric bootstrap, Bootstrap Çıkarımı	leave-one-out resampling, Quenouille-Tukey jackknife, delete-one jackknife, Jackknife Yeniden Örnekleme	randomization test, exact permutation test, re-randomization test, Permütasyon Testi
Liên quan	5	5	5
Tóm tắt	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.	The jackknife is a classical resampling method that estimates the bias and variance of a statistic by systematically recomputing it with one observation left out at a time. Introduced by Quenouille in 1956 and later reviewed by Miller in 1974, it predates the bootstrap and remains a simple, deterministic tool for assessing estimator stability.	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.