Abstract
In principle, weak convergence is the pointwise convergence of “operators” X α or L α on the space C b (D). However, there is automatically uniform convergence over certain subsets. These subsets can be fairly big: equicontinuity and boundedness suffice. On the other hand, there also exist small (countable) subsets such that pointwise convergence on such a subset is automatically uniform, and equivalent to pointwise convergence on the whole of C b (D), i.e. weak convergence. For separable D, it is even possible to pick such a countable subset that works for every X α , at the same time.
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© 1996 Springer Science+Business Media New York
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van der Vaart, A.W., Wellner, J.A. (1996). Uniformity and Metrization. In: Weak Convergence and Empirical Processes. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4757-2545-2_12
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DOI: https://doi.org/10.1007/978-1-4757-2545-2_12
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4757-2547-6
Online ISBN: 978-1-4757-2545-2
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