手法を比較

	ベイズブートストラップ（ルービン）	順列検定（ランダム化検定）
分野	統計学	統計学
系統	Regression model	Regression model
提唱年	1981	2005
提唱者	Rubin (1981); large-sample theory by Lo (1987)	Good (2005); Edgington & Onghena (2007); resampling tradition
種類	Resampling / posterior simulation	Nonparametric resampling test
原典	Rubin, D. B. (1981). The Bayesian Bootstrap. The Annals of Statistics, 9(1), 130-134.	Good, P. (2005). Permutation, Parametric and Bootstrap Tests of Hypotheses (3rd ed.). Springer. ISBN: 978-0387202792
別名	Bayesian Bootstrap (Rubin), Rubin bootstrap, Dirichlet-weighted bootstrap	randomization test, exact permutation test, re-randomization test, Permütasyon Testi
関連	5	5
概要	The Bayesian Bootstrap, introduced by Donald B. Rubin in 1981, is a resampling method that produces a Bayesian counterpart to the frequentist bootstrap by assigning each observation a random weight drawn from a Dirichlet distribution. It yields a full posterior distribution for a statistic and allows prior information to be incorporated.	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.