scholarly journals Asymptotic equivalence for pure jump Lévy processes with unknown Lévy density and Gaussian white noise

2016 ◽  
Vol 126 (2) ◽  
pp. 503-541 ◽  
Author(s):  
Ester Mariucci
Author(s):  
Cécile Penland ◽  
Brian D Ewald

Stochastic descriptions of multiscale interactions are more and more frequently found in numerical models of weather and climate. These descriptions are often made in terms of differential equations with random forcing components. In this article, we review the basic properties of stochastic differential equations driven by classical Gaussian white noise and compare with systems described by stable Lévy processes. We also discuss aspects of numerically generating these processes.


2004 ◽  
Vol 206 (1) ◽  
pp. 109-148 ◽  
Author(s):  
Giulia Di Nunno ◽  
Bernt Øksendal ◽  
Frank Proske

2018 ◽  
Vol 46 (6B) ◽  
pp. 3676-3706
Author(s):  
Cristina Butucea ◽  
Mădălin Guţă ◽  
Michael Nussbaum

2006 ◽  
Vol 98 (2) ◽  
pp. 237 ◽  
Author(s):  
Arne Løkka ◽  
Frank Norbert Proske

We develop a white noise calculus for pure jump Lévy processes on the Poisson space. This theory covers the treatment of Lévy processes of unbounded variation. The starting point of the theory is the construction of a distribution space. This space has many of the same nice properties as the classical Schwartz space, but is modified in a certain way in order to be more suitable for pure jump Lévy processes. We apply Minlos's theorem to this space and obtain a white noise measure which satisfies the first condition of analyticity, and which is non-degenerate. Furthermore, we obtain generalized Charlier polynomials for all Lévy measures. We introduce Kondratiev test function and distribution spaces, the $\mathcal{S}$-transform and the Wick product. We proceed by using a transfer principle on Poisson spaces to establish a differential calculus.


2017 ◽  
Vol 45 (6B) ◽  
pp. 4389-4418 ◽  
Author(s):  
Robert C. Dalang ◽  
Thomas Humeau

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