Glivenko–Cantelli Theorem and Bernstein–Kantorovich Invariance Principle

Svetlozar T. Rachev, Lev B. Klebanov, Stoyan V. Stoyanov and Frank J. Fabozzi
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Svetlozar T. Rachev: Stony Brook University, Department of Applied Mathematics and Statistics College of Business
Lev B. Klebanov: Charles University, Department of Probability and Statistics
Stoyan V. Stoyanov: EDHEC Business School EDHEC-Risk Institute
Frank J. Fabozzi: EDHEC Business School EDHEC-Risk Institute

Chapter Chapter 12 in The Methods of Distances in the Theory of Probability and Statistics, 2013, pp 283-296 from Springer

Abstract: Abstract This chapter begins with an application of the theory of probability metrics to the problem of convergence of the empirical probability measure.

Keywords: Limit Theorem; Polygonal Line; Probability Metrics; Wiener Measure; Functional Central Limit Theorem (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4614-4869-3_12

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DOI: 10.1007/978-1-4614-4869-3_12

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