手法を比較

	ベイズブートストラップ（ルービン）	フィッシャーの正確確率検定（Fisher Exact Randomization Inference）
分野	統計学	統計学
系統	Regression model	Regression model
提唱年	1981	1935
提唱者	Rubin (1981); large-sample theory by Lo (1987)	Ronald A. Fisher
種類	Resampling / posterior simulation	Exact permutation-based inference
原典	Rubin, D. B. (1981). The Bayesian Bootstrap. The Annals of Statistics, 9(1), 130-134.	Fisher, R. A. (1935). The Design of Experiments. Oliver & Boyd.
別名	Bayesian Bootstrap (Rubin), Rubin bootstrap, Dirichlet-weighted bootstrap	fisher randomization test, permutation inference, exact randomization test, randomizasyon çıkarımı (fisher exact randomization)
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.	Randomization inference, introduced by Ronald A. Fisher in The Design of Experiments (1935), computes an exact p-value by evaluating a test statistic across all possible treatment assignments under Fisher's sharp null hypothesis. It is regarded as the gold standard for analysing designed experiments because its validity rests on the known assignment mechanism rather than on distributional assumptions.