Abstract
Assume that Tn = Tn (ξ1,...,ξn,F) is a function of an i.i.d. sample and its underlying d.f.F. The importance of statistical large sample theory comes from the fact that the law ℒ(Tn) of Tn in many situations is not available, but may well be approximated by some normal distribution, say.
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References (and further reading)
Bickel, P.J. and Freedman, D.A. (1981). Some asymptotic theory for the bootstrap. Ann. Statist. 9, 1196–1217.
Efron, B. (1979). Bootstrap methods: another look at the jackknife. Ann. Statist. 7, 1–26.
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Klenk, A. and Stute, W. (1987). Bootstrapping of Lrestimates. Statist, and Decis. 5, 77–87.
Singh, K. (1981). On the asymptotic accuracy of Efron’s bootstrap. Ann. Statist. 9, 1187–1195.
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© 1987 Springer Basel AG
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Gaenssler, P., Stute, W. (1987). Bootstrapping. In: Seminar on Empirical Processes. DMV Seminar, vol 9. Birkhäuser, Basel. https://doi.org/10.1007/978-3-0348-6269-1_8
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DOI: https://doi.org/10.1007/978-3-0348-6269-1_8
Publisher Name: Birkhäuser, Basel
Print ISBN: 978-3-7643-1921-2
Online ISBN: 978-3-0348-6269-1
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