Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Bayesian Bootstrap (Rubin)× | Usanifu wa vitalu (Vitalu vinavyohamia na vilivyosimama)× | Kipimo cha Mgeuzo (Ubaguzi)× | |
|---|---|---|---|
| Nyanja | Takwimu | Takwimu | Takwimu |
| Familia | Regression model | Regression model | Regression model |
| Mwaka wa asili≠ | 1981 | 1989 | 2005 |
| Mwanzilishi≠ | Rubin (1981); large-sample theory by Lo (1987) | Künsch (moving block, 1989); Politis & Romano (stationary, 1994) | Good (2005); Edgington & Onghena (2007); resampling tradition |
| Aina≠ | Resampling / posterior simulation | Resampling inference for dependent data | Nonparametric resampling test |
| Chanzo asilia≠ | Rubin, D. B. (1981). The Bayesian Bootstrap. The Annals of Statistics, 9(1), 130-134. DOI ↗ | 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 |
| Majina mbadala≠ | Bayesian Bootstrap (Rubin), Rubin bootstrap, Dirichlet-weighted bootstrap | moving block bootstrap, stationary bootstrap, blok bootstrap (moving block / stationary) | randomization test, exact permutation test, re-randomization test, Permütasyon Testi |
| Zinazohusiana | 5 | 5 | 5 |
| Muhtasari≠ | 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. | 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. |
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