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2013 | OriginalPaper | Chapter

20. Functional Limit Theorems

Author : Alexandr A. Borovkov

Published in: Probability Theory

Publisher: Springer London

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Abstract

The chapter begins with Sect. 20.1 presenting the classical Functional Central Limit Theorem in the triangular array scheme. It establishes not only convergence of the distributions of the scaled trajectories of random walks to that of the Wiener process, but also convergence rates for Lipshchitz sets and distribution functions of Lipshchitz functionals in the case of finite third moments when the Lyapunov condition is met. Section 20.2 uses the Law of the Iterated Logarithm for the Wiener process to establish such a low for the trajectory of a random walk with independent non-identically distributed jumps. Section 20.3 is devoted to proving convergence to the Poisson process of the processes of cumulative sums of independent random indicators with low success probabilities and also that of the so-called thinning renewal processes.

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Footnotes
1
The extension of the approach to proving the central limit theorem used in Sect. 8.​5, which is used in this demonstration, was suggested by A.V. Sakhanenko.
 
Literature
1.
go back to reference Billingsley, P.: Convergence of Probability Measures. Wiley, New York (1968) Billingsley, P.: Convergence of Probability Measures. Wiley, New York (1968)
14.
go back to reference Gikhman, I.I., Skorokhod, A.V.: Introduction to the Theory of Random Processes. Saunders, Philadelphia (1969) Gikhman, I.I., Skorokhod, A.V.: Introduction to the Theory of Random Processes. Saunders, Philadelphia (1969)
32.
go back to reference Skorokhod, A.V.: Random Processes with Independent Increments. Kluwer Academic, Dordrecht (1991) Skorokhod, A.V.: Random Processes with Independent Increments. Kluwer Academic, Dordrecht (1991)
Metadata
Title
Functional Limit Theorems
Author
Alexandr A. Borovkov
Copyright Year
2013
Publisher
Springer London
DOI
https://doi.org/10.1007/978-1-4471-5201-9_20