Proves that Lévy-driven linear equations p(D)s = q(D)ḊL admit measurable solutions in Besov spaces and that semilinear versions p(D)u = g(·,u) + ḊL have measurable solutions in weighted Besov spaces when g is Lipschitz.
L\'evy-driven causal CARMA random fields
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abstract
We introduce L\'evy-driven causal CARMA random fields on $\mathbb{R}^d$, extending the class of CARMA processes. The definition is based on a system of stochastic partial differential equations which generalize the classical state-space representation of CARMA processes. The resulting CARMA model differs fundamentally from the isotropic CARMA random field of Brockwell and Matsuda. We show existence of the model under mild assumptions and examine some of its features including the second-order structure and path properties. In particular, we investigate the sampling behavior and formulate conditions for the causal CARMA random field to be an ARMA random field when sampled on an equidistant lattice.
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math.PR 1years
2019 1verdicts
UNVERDICTED 1representative citing papers
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L\'{e}vy driven linear and semilinear stochastic partial differential equations
Proves that Lévy-driven linear equations p(D)s = q(D)ḊL admit measurable solutions in Besov spaces and that semilinear versions p(D)u = g(·,u) + ḊL have measurable solutions in weighted Besov spaces when g is Lipschitz.