1982
DOI: 10.2307/1427027
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On simulation from infinitely divisible distributions

Abstract: A general method based on a limit theorem for generation of random numbers from infinitely divisible distributions with essentially given Lévy measure is studied. Some classes of infinitely divisible distributions that appear in a natural way in this context are paid particular attention.

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Cited by 122 publications
(63 citation statements)
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“…By applying the generalized shot noise method [6,33], we get the desired series representation. To prove the claim for {X 2,n } n∈N , consider the probability measure on…”
Section: Resultsmentioning
confidence: 99%
“…By applying the generalized shot noise method [6,33], we get the desired series representation. To prove the claim for {X 2,n } n∈N , consider the probability measure on…”
Section: Resultsmentioning
confidence: 99%
“…Both [14] and [3] describe how to simulate shot-noise Cox processes using the techniques developed in [2]. Just as with the simple cluster process model it is necessary to simulate ζ on a larger region than W , but furthermore it is only possible to simulate a finite number of atoms in any bounded area (see [3] for a further discussion of this).…”
Section: The General Methodsmentioning
confidence: 99%
“…We solved the WM propagator by a second-order implicit-explicit (IMEX) time splitting scheme. 7 For spatial discretization we used the Fourier collocation method. The reference solution was established by running the Burgers equation with ξ taking all the possible values.…”
Section: The Burgers Equation With One Rvmentioning
confidence: 99%
“…. , ξ d ) is meaningful to be considered because many stochastic processes have series representations, e.g., Karhunen-Loeve expansion for the Gaussian process[24,32], and shot noise expansion for Levy pure jump processes[7,43,44].Downloaded 10/07/15 to 18.111.37.34. Redistribution subject to SIAM license or copyright; see http://www.siam.org/journals/ojsa.php…”
mentioning
confidence: 99%