Journal of Applied Probability

Moderate deviation principle for a class of stochastic partial differential equations

Parisa Fatheddin and Jie Xiong

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Abstract

We establish the moderate deviation principle for the solutions of a class of stochastic partial differential equations with non-Lipschitz continuous coefficients. As an application, we derive the moderate deviation principle for two important population models: super-Brownian motion and the Fleming-Viot process.

Article information

Source
J. Appl. Probab., Volume 53, Number 1 (2016), 279-292.

Dates
First available in Project Euclid: 8 March 2016

Permanent link to this document
https://projecteuclid.org/euclid.jap/1457470574

Mathematical Reviews number (MathSciNet)
MR3471962

Zentralblatt MATH identifier
1337.60043

Subjects
Primary: 60F10: Large deviations
Secondary: 60H15: Stochastic partial differential equations [See also 35R60] 60J68: Superprocesses

Keywords
Moderate deviation principle Fleming-Viot process stochastic partial differential equation super-Brownian motion

Citation

Fatheddin, Parisa; Xiong, Jie. Moderate deviation principle for a class of stochastic partial differential equations. J. Appl. Probab. 53 (2016), no. 1, 279--292. https://projecteuclid.org/euclid.jap/1457470574


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