Markov Jump Processes Approximating a Non-Symmetric Generalized Diffusion
Consider a non-symmetric generalized diffusion X (⋅) in ℝ d determined by the differential operator . In this paper the diffusion process is approximated by Markov jump processes X n (⋅), in homogeneous and isotropic grids G n ⊂ℝ d , which converge in distribution in the Skorokhod space D ([0,∞),ℝ d...
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Veröffentlicht in: | Applied mathematics & optimization 2011-08, Vol.64 (1), p.101-133 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Consider a non-symmetric generalized diffusion
X
(⋅) in ℝ
d
determined by the differential operator
. In this paper the diffusion process is approximated by Markov jump processes
X
n
(⋅), in homogeneous and isotropic grids
G
n
⊂ℝ
d
, which converge in distribution in the Skorokhod space
D
([0,∞),ℝ
d
) to the diffusion
X
(⋅). The generators of
X
n
(⋅) are constructed explicitly. Due to the homogeneity and isotropy of grids, the proposed method for
d
≥3 can be applied to processes for which the diffusion tensor
fulfills an additional condition. The proposed construction offers a simple method for simulation of sample paths of non-symmetric generalized diffusion. Simulations are carried out in terms of jump processes
X
n
(⋅). For piece-wise constant functions
a
ij
on ℝ
d
and piece-wise continuous functions
a
ij
on ℝ
2
the construction and principal algorithm are described enabling an easy implementation into a computer code. |
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ISSN: | 0095-4616 1432-0606 |
DOI: | 10.1007/s00245-011-9133-1 |