Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Bootstrap bayesiano (Rubin)× | Prueba de permutación (aleatorización)× | |
|---|---|---|
| Campo | Estadística | Estadística |
| Familia | Regression model | Regression model |
| Año de origen≠ | 1981 | 2005 |
| Autor original≠ | Rubin (1981); large-sample theory by Lo (1987) | Good (2005); Edgington & Onghena (2007); resampling tradition |
| Tipo≠ | Resampling / posterior simulation | Nonparametric resampling test |
| Fuente seminal≠ | Rubin, D. B. (1981). The Bayesian Bootstrap. The Annals of Statistics, 9(1), 130-134. DOI ↗ | Good, P. (2005). Permutation, Parametric and Bootstrap Tests of Hypotheses (3rd ed.). Springer. ISBN: 978-0387202792 |
| Alias≠ | Bayesian Bootstrap (Rubin), Rubin bootstrap, Dirichlet-weighted bootstrap | randomization test, exact permutation test, re-randomization test, Permütasyon Testi |
| Relacionados | 5 | 5 |
| Resumen≠ | 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. | 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. |
| ScholarGateConjunto de datos ↗ |
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