Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Bootstrap pe blocuri (blocuri mobile și staționare)× | Testul de permutare (randomizare)× | |
|---|---|---|
| Domeniu | Statistică | Statistică |
| Familie | Regression model | Regression model |
| Anul apariției≠ | 1989 | 2005 |
| Autorul original≠ | Künsch (moving block, 1989); Politis & Romano (stationary, 1994) | Good (2005); Edgington & Onghena (2007); resampling tradition |
| Tip≠ | Resampling inference for dependent data | Nonparametric resampling test |
| Sursa seminală≠ | Künsch, H. R. (1989). The Jackknife and the Bootstrap for General Stationary Observations. Annals of Statistics, 17(3), 1217-1241. DOI ↗ | Good, P. (2005). Permutation, Parametric and Bootstrap Tests of Hypotheses (3rd ed.). Springer. ISBN: 978-0387202792 |
| Denumiri alternative≠ | moving block bootstrap, stationary bootstrap, blok bootstrap (moving block / stationary) | randomization test, exact permutation test, re-randomization test, Permütasyon Testi |
| Înrudite | 5 | 5 |
| Rezumat≠ | Block bootstrap is a resampling method for dependent, autocorrelated time-series data: instead of resampling single observations, it resamples whole blocks of consecutive observations so the serial-correlation structure is preserved. The moving block variant was introduced by Künsch (1989) and the stationary variant by Politis and Romano (1994). | 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. |
| ScholarGateSet de date ↗ |
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