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A Note on Conditional Versus Joint Unconditional Weak Convergence in Bootstrap Consistency Results

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Abstract

The consistency of a bootstrap or resampling scheme is classically validated by weak convergence of conditional laws. However, when working with stochastic processes in the space of bounded functions and their weak convergence in the Hoffmann–Jørgensen sense, an obstacle occurs: due to possible non-measurability, neither laws nor conditional laws are well defined. Starting from an equivalent formulation of weak convergence based on the bounded Lipschitz metric, a classical circumvention is to formulate bootstrap consistency in terms of the latter distance between what might be called a conditional law of the (non-measurable) bootstrap process and the law of the limiting process. The main contribution of this note is to provide an equivalent formulation of bootstrap consistency in the space of bounded functions which is more intuitive and easy to work with. Essentially, the equivalent formulation consists of (unconditional) weak convergence of the original process jointly with two bootstrap replicates. As a by-product, we provide two equivalent formulations of bootstrap consistency for statistics taking values in separable metric spaces: the first in terms of (unconditional) weak convergence of the statistic jointly with its bootstrap replicates, the second in terms of convergence in probability of the empirical distribution function of the bootstrap replicates. Finally, the asymptotic validity of bootstrap-based confidence intervals and tests is briefly revisited, with particular emphasis on the (in practice, unavoidable) Monte Carlo approximation of conditional quantiles.

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Acknowledgements

The authors are very grateful to an anonymous referee for making them aware of “Hoeffding’s trick” [19] and for several other very relevant suggestions which contributed to significantly increasing the scope of this note. The authors would also like to thank Jean-David Fermanian for fruitful discussions. This research has been supported by the Collaborative Research Center “Statistical modeling of nonlinear dynamic processes” (SFB 823) of the German Research Foundation, which is gratefully acknowledged.

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Authors and Affiliations

  1. Fakultät für Mathematik, Ruhr-Universität Bochum, Universitätsstr. 150, 44780, Bochum, Germany

    Axel Bücher

  2. Laboratoire de Mathématiques et Applications – IPRA, UMR 5142, CNRS/Université de Pau et des Pays de l’Adour, B.P. 1155, 64013, Pau Cedex, France

    Ivan Kojadinovic

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  1. Axel Bücher
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  2. Ivan Kojadinovic
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Correspondence to Axel Bücher.

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Bücher, A., Kojadinovic, I. A Note on Conditional Versus Joint Unconditional Weak Convergence in Bootstrap Consistency Results. J Theor Probab 32, 1145–1165 (2019). https://doi.org/10.1007/s10959-018-0823-3

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  • DOI: https://doi.org/10.1007/s10959-018-0823-3

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