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Some Asymptotic Theory for the Bootstrap
The Annals of Statistics · 1981 · Vol. 9(6)
Abstract
Efron's "bootstrap" method of distribution approximation is shown to be asymptotically valid in a large number of situations, including $t$-statistics, the empirical and quantile processes, and von Mises functionals. Some counter-examples are also given, to show that the approximation does not always succeed.
Bayesian Methods and Mixture ModelsStatistical Methods and InferenceMarkov Chains and Monte Carlo MethodsMathematicsQuantileAsymptotic analysisApplied mathematicsAsymptotic distributionDistribution (mathematics)StatisticsEconometricsMathematical analysisEstimator
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References
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On the Asymptotic Accuracy of Efron's Bootstrap
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