Large deviations for sample paths of Gaussian processes quadratic variations.
Perrin, O., Zani, M. (2005)
Zapiski Nauchnykh Seminarov POMI
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Displaying similar documents to “Identities in law between quadratic functionals of bivariate Gaussian processes, through Fubini theorems and symmetric projections”
Large deviations for sample paths of Gaussian processes quadratic variations.
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T. Mikosch (1988)
Monatshefte für Mathematik
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Enhanced Gaussian processes and applications
Laure Coutin, Nicolas Victoir (2009)
ESAIM: Probability and Statistics
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We propose some construction of enhanced Gaussian processes using Karhunen-Loeve expansion. We obtain a characterization and some criterion of existence and uniqueness. Using rough-path theory, we derive some Wong-Zakai Theorem.
Invariance principle, multifractional gaussian processes and long-range dependence
Serge Cohen, Renaud Marty (2008)
Annales de l'I.H.P. Probabilités et statistiques
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This paper is devoted to establish an invariance principle where the limit process is a multifractional gaussian process with a multifractional function which takes its values in (1/2, 1). Some properties, such as regularity and local self-similarity of this process are studied. Moreover the limit process is compared to the multifractional brownian motion.
A type of Gauss' divergence formula on Wiener spaces.
Otobe, Yoshiki (2009)
Electronic Communications in Probability [electronic only]
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Large deviation principle for enhanced gaussian processes
Peter Friz, Nicolas Victoir (2007)
Annales de l'I.H.P. Probabilités et statistiques
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Weighted power variations of iterated Brownian motion.
Nourdin, Ivan, Peccati, Giovanni (2008)
Electronic Journal of Probability [electronic only]
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On the small deviation problem for some iterated processes.
Aurzada, Frank, Lifshits, Mikhail (2009)
Electronic Journal of Probability [electronic only]
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Linear transformations of Wiener process that born Wiener process, Brownian bridge or Ornstein-Uhlenbeck process
Petr Lachout (2001)
Kybernetika
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The paper presents a discussion on linear transformations of a Wiener process. The considered processes are collections of stochastic integrals of non-random functions w.r.t. Wiener process. We are interested in conditions under which the transformed process is a Wiener process, a Brownian bridge or an Ornstein –Uhlenbeck process.