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L1-Norm of Infinitely Divisible Random Vectors and Certain Stochastic Integrals
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Michael B. Marcus, The City College of CUNY Jan Rosinski, University of Tennessee |
Abstract
Equivalent upper and lower bounds for the L1
norm of Hilbert space valued infinitely divisible random variables are
obtained and
used to find bounds for different types of stochastic integrals.
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Full text: PDF
Pages: 15-29
Published on: January 10, 2001
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Bibliography
-
De la Pena, V.H. and Gine, E. (1999),
Decoupling. From dependence to independence.
Springer-Verlag, New York.
Math. Review 99k:60044
-
Dunford, N and Schwartz, J.T. (1958),
Linear Operators, Part I: General Theory.Decoupling.
Wiley, New York.
Math. Review 90g:47001a
-
I.I. Gihman and A.V. Skorohod. (1975),
The theory of Stochastic Processes, Vol. 2.
Springer, Berlin.
Math. Review 51:11656
-
Klass, M.J. (1980),
Precision bounds for the relative error in the approximation of
E|S_n| and extensions.
Ann. Probab. 8, 350--367.
Math. Review 82h:60097
-
Kwapien, S. and Woyczynski, W.A. (1992),
Random Series and Stochastic Integrals: Single and Multiple.
Birkh"auser, Boston.
Math. Review 94k:60074
-
Marcus, M.B. and Rosinski, J.
Continuity of stochastic integrals with respect to
infinitely divisible random measures.
2000 (preprint) Math. Review number not available.
-
Parthasarathy, K.R. (1967),
Probability measures on metric spaces.
Academic Press, New York.
Math. Review 37:2271
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Electronic Communications in Probability. ISSN: 1083-589X |
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