Jämför metoder
Granska de valda metoderna sida vid sida; rader som skiljer sig är markerade.
| Block Bootstrap (Moving Block och Stationary)× | Bootstrapinferens× | Permutationstest (Randomiseringstest)× | |
|---|---|---|---|
| Ämnesområde | Statistik | Statistik | Statistik |
| Familj | Regression model | Regression model | Regression model |
| Ursprungsår≠ | 1989 | 1979 | 2005 |
| Upphovsperson≠ | Künsch (moving block, 1989); Politis & Romano (stationary, 1994) | Bradley Efron | Good (2005); Edgington & Onghena (2007); resampling tradition |
| Typ≠ | Resampling inference for dependent data | Resampling-based inference | Nonparametric resampling test |
| Ursprungskälla≠ | Künsch, H. R. (1989). The Jackknife and the Bootstrap for General Stationary Observations. Annals of Statistics, 17(3), 1217-1241. DOI ↗ | Efron, B. (1979). Bootstrap Methods: Another Look at the Jackknife. Annals of Statistics, 7(1), 1-26. DOI ↗ | Good, P. (2005). Permutation, Parametric and Bootstrap Tests of Hypotheses (3rd ed.). Springer. ISBN: 978-0387202792 |
| Alias≠ | moving block bootstrap, stationary bootstrap, blok bootstrap (moving block / stationary) | bootstrap, bootstrap resampling, nonparametric bootstrap, Bootstrap Çıkarımı | randomization test, exact permutation test, re-randomization test, Permütasyon Testi |
| Närliggande | 5 | 5 | 5 |
| Sammanfattning≠ | 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). | Bootstrap inference, introduced by Bradley Efron in 1979, estimates the sampling distribution of a statistic by repeatedly resampling the observed data with replacement. It requires no distributional assumption and produces reliable confidence intervals even in small samples. | 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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