arXiv:1302.4011 [math.PR]AbstractReferencesReviewsResources
Approximation of stable random measures and applications to linear fractional stable integrals
Published 2013-02-16Version 1
Using lattice approximations of Euclidean space, we develop a way to approximate stable processes that are represented by stochastic integrals over Euclidean space. Via a stable version of the Lindeberg-Feller Theorem we show that the approximations weakly converge as the mesh-size goes to zero. As an application, we improve upon previous approximation schemes for integrals with respect to linear fractional stable motions.
Comments: 18 pages
Categories: math.PR
Related articles: Most relevant | Search more
Marginals of multivariate Gibbs distributions with applications in Bayesian species sampling
Applications of a simple but useful technique to stochastic convolution of $α$-stable processes
Takacs' asymptotic theorem and its applications: A survey