of i.i.d. random variables such that EX s 0, let 1 2 Z be a random variable possessing a stable distribution G with exponent ␣, 1 -␣ F 2, assume the distribution of X is attracted to G, and set S s X n 1 q иии qX . We prove that n p Ž ␣ p rŽ ␣yp..Ž r r py1. r r py2 1 r p yŽ ␣ p rŽ ␣yp..Ž r r py1.
Convergence of Weighted Sums and Laws of Large Numbers in D([0,1]; E)
✍ Scribed by I. Schiopukratina; P. Daffer
- Publisher
- Elsevier Science
- Year
- 1995
- Tongue
- English
- Weight
- 426 KB
- Volume
- 53
- Category
- Article
- ISSN
- 0047-259X
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✦ Synopsis
Convergence properties of weighted sums of functions in (D([0,1] ; E)(E) a Banach space) are investigated. We show that convergence in the Skorokhod (J_{1})-topology of a sequence (\left(x_{n}\right)) in (D([0,1] ; E)) does not imply convergence of a sequence (\left(\bar{x}{n}\right)) of averages. Convergence in the (J{1})-topology of a sequence (\left(\bar{x}{n}\right)) of averages is shown, under the growth condition (\left|x{n}\right|{\infty}=o(n)), to be equivalent to the convergence of (\left(\bar{x}{n}\right)) in the uniform topology. Convergence of a sequence (\left(x_{n}\right)) is shown to imply convergence of the sequence (\left(\bar{x}{n}\right)) of averages in the (M{1}) and (M_{2}) topologies. The strong law of large numbers in (D[0,1]) is considered and an example is constructed to show that different definitions of the strong law of large numbers are nonequivalent. 1995 Academic Press, Inc.
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