Salīdzināt metodes

	Džeknaifa atkārtotā izlases metode	Permutācijas (randomizācijas) tests
Nozare	Statistika	Statistika
Saime	Regression model	Regression model
Izcelsmes gads	1956	2005
Autors	Quenouille (1956); reviewed by Miller (1974)	Good (2005); Edgington & Onghena (2007); resampling tradition
Tips	Resampling / bias and variance estimation	Nonparametric resampling test
Pirmavots	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
Citi nosaukumi	leave-one-out resampling, Quenouille-Tukey jackknife, delete-one jackknife, Jackknife Yeniden Örnekleme	randomization test, exact permutation test, re-randomization test, Permütasyon Testi
Saistītās	5	5
Kopsavilkums	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.