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Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.

Dublā (iterētā) bootstrap metode×Permutācijas (randomizācijas) tests×
NozareStatistikaStatistika
SaimeRegression modelRegression model
Izcelsmes gads19862005
AutorsHall (1986); Beran (1987)Good (2005); Edgington & Onghena (2007); resampling tradition
TipsResampling calibration (nested bootstrap)Nonparametric resampling test
PirmavotsHall, P. (1986). On the Bootstrap and Confidence Intervals. Annals of Statistics, 14(4), 1431-1452. DOI ↗Good, P. (2005). Permutation, Parametric and Bootstrap Tests of Hypotheses (3rd ed.). Springer. ISBN: 978-0387202792
Citi nosaukumiiterated bootstrap, nested bootstrap, calibrated bootstrap, Çift Bootstrap (Double / Iterated Bootstrap)randomization test, exact permutation test, re-randomization test, Permütasyon Testi
Saistītās55
KopsavilkumsThe double bootstrap is a resampling method that calibrates a bootstrap confidence interval with a second, nested layer of bootstrap to bring its actual coverage closer to the nominal level. Introduced by Hall (1986) and Beran (1987), it is especially valuable for small samples and skewed distributions where a single-layer bootstrap under-covers.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.
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ScholarGateSalīdzināt metodes: Double Bootstrap · Permutation Test. Izgūts 2026-06-15 no https://scholargate.app/lv/compare