Abstract
The methods of the theory of weak convergence of probability measures are of wide use in many areas of applications to statistics, operations research and stochastic control theory, where it is convenient or useful to approximate a process by a sequence of other processes or vice versa. The theory is treated thoroughly in Billingsley [B1], and here we only mention some of the ideas which are of particular use in the sequel. The theory is an extension of the concept of convergence in distribution to sequences of abstract valued random variables.
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© 1978 Springer-Verlag New York, Inc.
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Kushner, H.J., Clark, D.S. (1978). Weak Convergence of Probability Measures. In: Stochastic Approximation Methods for Constrained and Unconstrained Systems. Applied Mathematical Sciences, vol 26. Springer, New York, NY. https://doi.org/10.1007/978-1-4684-9352-8_3
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DOI: https://doi.org/10.1007/978-1-4684-9352-8_3
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-90341-5
Online ISBN: 978-1-4684-9352-8
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