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Bootstrap of deviation probabilities with applications

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  • Dasgupta, Ratan

Abstract

We show that under different moment bounds on the underlying variables, bootstrap approximation to the large deviation probabilities of standardized sample sum, based on independent random variables, is valid for a wider zone of n, the sample size, compared to the classical normal tail probability approximation. As an application, different notions of efficiency for statistical tests are considered from Bayesian point of view. In particular, efficiency due to Pitman (1938) [11], Chernoff (1952) [1], and Bayes risk efficiency due to Rubin and Sethuraman (1965) [12] turn out to be special cases with the choice of the weight function; i.e., prior density times loss.

Suggested Citation

  • Dasgupta, Ratan, 2010. "Bootstrap of deviation probabilities with applications," Journal of Multivariate Analysis, Elsevier, vol. 101(9), pages 2137-2148, October.
    • Handle: RePEc:eee:jmvana:v:101:y:2010:i:9:p:2137-2148
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    Cited by:

    1. Sergio Alvarez-Andrade & Salim Bouzebda, 2020. "Cramér’s type results for some bootstrapped U-statistics," Statistical Papers, Springer, vol. 61(4), pages 1685-1699, August.
    2. Radulovic, Dragan, 2012. "A direct bootstrapping technique and its application to a novel goodness of fit test," Journal of Multivariate Analysis, Elsevier, vol. 107(C), pages 181-199.
    3. Withers, Christopher S. & Nadarajah, Saralees, 2013. "Bayesian efficiency," Statistics & Probability Letters, Elsevier, vol. 83(4), pages 1203-1212.

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