Linganisha mbinu

	Usanifu wa Bootstrap wa Kigezo (Parametric Bootstrap)	Bayesian Bootstrap (Rubin)	Utoaji wa Hitimisho kwa Njia ya Bootstrap
Nyanja	Takwimu	Takwimu	Takwimu
Familia	Regression model	Regression model	Regression model
Mwaka wa asili	1993	1981	1979
Mwanzilishi	Efron & Tibshirani; Davison & Hinkley	Rubin (1981); large-sample theory by Lo (1987)	Bradley Efron
Aina	Resampling-based inference (model-based)	Resampling / posterior simulation	Resampling-based inference
Chanzo asilia	Efron, B. & Tibshirani, R. J. (1993). An Introduction to the Bootstrap. CRC Press. ISBN: 978-0412042317	Rubin, D. B. (1981). The Bayesian Bootstrap. The Annals of Statistics, 9(1), 130-134.	Efron, B. (1979). Bootstrap Methods: Another Look at the Jackknife. Annals of Statistics, 7(1), 1-26.
Majina mbadala	parametrik bootstrap, model-based bootstrap, parametric resampling	Bayesian Bootstrap (Rubin), Rubin bootstrap, Dirichlet-weighted bootstrap	bootstrap, bootstrap resampling, nonparametric bootstrap, Bootstrap Çıkarımı
Zinazohusiana	5	5	5
Muhtasari	The parametric bootstrap is a resampling method that estimates standard errors and confidence intervals by drawing repeated samples from a parametric model that has been fitted to the data. Developed in the bootstrap literature of Efron and Tibshirani (1993) and Davison and Hinkley (1997), it replaces analytic derivations for non-normal distributions and complex statistics.	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.	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.