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Volterra-type Ornstein–Uhlenbeck processes in space and time

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  • Pham, Viet Son
  • Chong, Carsten

Abstract

We propose a novel class of temporo-spatial Ornstein–Uhlenbeck processes as solutions to Lévy-driven Volterra equations with additive noise and multiplicative drift. After formulating conditions for the existence and uniqueness of solutions, we derive an explicit solution formula and discuss distributional properties such as stationarity, second-order structure and short versus long memory. Furthermore, we analyze in detail the path properties of the solution process. In particular, we introduce different notions of càdlàg paths in space and time and establish conditions for the existence of versions with these regularity properties. The theoretical results are accompanied by illustrative examples.

Suggested Citation

  • Pham, Viet Son & Chong, Carsten, 2018. "Volterra-type Ornstein–Uhlenbeck processes in space and time," Stochastic Processes and their Applications, Elsevier, vol. 128(9), pages 3082-3117.
    • Handle: RePEc:eee:spapps:v:128:y:2018:i:9:p:3082-3117
    DOI: 10.1016/j.spa.2017.10.012
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    1. Peter J. Brockwell & Yasumasa Matsuda, 2017. "Continuous auto-regressive moving average random fields on ℝ-super-n," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(3), pages 833-857, June.
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    Cited by:

    1. Pham, Viet Son, 2020. "Lévy-driven causal CARMA random fields," Stochastic Processes and their Applications, Elsevier, vol. 130(12), pages 7547-7574.

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