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We investigate the small deviation probabilities of a class of very smooth stationary Gaussian processes playing an important role in Bayesian statistical inference. Our calculations are based on the appropriate modification of the entropy…

Probability · Mathematics 2010-06-22 F. Aurzada , I. A. Ibragimov , M. A. Lifshits , J. H. van Zanten

We study the small deviation probabilities of a family of very smooth self-similar Gaussian processes. The canonical process from the family has the same scaling property as standard Brownian motion and plays an important role in the study…

Probability · Mathematics 2011-08-18 Frank Aurzada , Fuchang Gao , Thomas Kühn , Wenbo V. Li , Qi-Man Shao

We investigate the Large Deviation behavior in small time of continuous Gaussian processes. We introduce a general procedure allowing to derive Large Deviation Principles in small time starting from the well understood context of Large…

Probability · Mathematics 2023-01-11 Paolo Baldi , Barbara Pacchiarotti

In this article we prove large deviations principles for high minima of Gaussian processes with nonnegatively correlated increments on arbitrary intervals. Furthermore, we prove large deviations principles for the increments of such…

Probability · Mathematics 2024-04-08 Zachary Selk

We obtain several extensions of Talagrand's lower bound for the small deviation probability using metric entropy. For Gaussian processes, our investigations are focused on processes with sub-polynomial and, respectively, exponential…

Probability · Mathematics 2008-11-14 Frank Aurzada , Mikhail Lifshits

We study the small deviation problem $\log\mathbb{P}(\sup_{t\in[0,1]}|X_t|\leq\varepsilon)$, as $\varepsilon\to0$, for general L\'{e}vy processes $X$. The techniques enable us to determine the asymptotic rate for general real-valued…

Probability · Mathematics 2009-09-25 Frank Aurzada , Steffen Dereich

The main results in this paper concern large deviations for families of non-Gaussian processes obtained as suitable perturbations of continuous centered multivariate Gaussian processes which satisfy a large deviation principle. We present…

Probability · Mathematics 2023-07-06 C. Macci , B. Pacchiarotti

A moderate deviation principle for nonlinear functions of Gaussian processes is established. The nonlinear functions need not be locally bounded. Especially, the logarithm is allowed. (Thus, small deviations of the process are relevant.)…

Probability · Mathematics 2007-05-23 Boris Tsirelson

Letting~$N=\left\{N(t), t\geq0\right\}$ be a standard Poisson process, Stroock~ \cite{Stroock-1981} constructed a family of continuous processes by $$\Theta_{\epsilon}(t)=\int_0^t\theta_{\epsilon}(r)dr, \ \ \ \ \ 0 \le t \le 1,$$ where…

Probability · Mathematics 2022-06-06 Hui Jiang , Lihu Xu , Qingshan Yang

We study large deviation principles for Gaussian processes lifted to the free nilpotent group of step N. We apply this to a large class of Gaussian processes lifted to geometric rough paths. A large deviation principle for enhanced…

Probability · Mathematics 2007-05-23 Peter Friz , Nicolas Victoir

The entropy of an ergodic finite-alphabet process can be computed from a single typical sample path x_1^n using the entropy of the k-block empirical probability and letting k grow with $n$ roughly like log n. We further assume that the…

Probability · Mathematics 2009-11-10 J. -R. Chazottes , D. Gabrielli

The large deviation function for entropy production is calculated for a particle driven along a periodic potential by solving a time-independent eigenvalue problem. In an intermediate force regime, the large deviation function shows…

Statistical Mechanics · Physics 2009-01-15 Jakob Mehl , Thomas Speck , Udo Seifert

In this paper we describe the alternative approach to the sample boundedness and continuity of stochastic processes. We show that the regularity of paths can be understood in terms of a distribution of the argument maximum. For a centered…

Probability · Mathematics 2012-11-19 Witold Bednorz

Under certain mild conditions, some limit theorems for functionals of two independent Gaussian processes are obtained. The results apply to general Gaussian processes including fractional Brownian motion, sub-fractional Brownian motion and…

Probability · Mathematics 2018-01-30 Jian Song , Fangjun Xu , Qian Yu

We investigate small deviation properties of Gaussian random fields in the space $L_q(\R^N,\mu)$ where $\mu$ is an arbitrary finite compactly supported Borel measure. Of special interest are hereby "thin" measures $\mu$, i.e., those which…

Probability · Mathematics 2007-05-23 Mikhail Lifshits , Werner Linde , Zhan Shi

The paper deals with the asymptotic behavior of the bridge of a Gaussian process conditioned to stay in $n$ fixed points at $n$ fixed past instants. In particular, functional large deviation results are stated for small time. Several…

Probability · Mathematics 2016-04-06 L. Caramellino , B. Pacchiarotti

Employing the optimal fluctuation method (OFM), we study the large deviation function of long-time averages $(1/T)\int_{-T/2}^{T/2} x^n(t) dt$, $n=1,2, \dots$, of centered stationary Gaussian processes. These processes are correlated and,…

Statistical Mechanics · Physics 2021-12-13 Baruch Meerson

A general class of non-Markov, supercritical Gaussian branching particle systems is introduced and its long-time asymptotics is studied. Both weak and strong laws of large numbers are developed with the limit object being characterized in…

Probability · Mathematics 2018-07-30 Michael A. Kouritzin , Khoa Lê , Deniz Sezer

We establish the Level-1 and Level-3 Large Deviation Principles (LDPs) for invariant measures on shift spaces over finite alphabets under very general decoupling conditions for which the thermodynamic formalism does not apply. Such…

Mathematical Physics · Physics 2019-06-28 Noé Cuneo , Vojkan Jakšić , Claude-Alain Pillet , Armen Shirikyan

We consider the small deviation probabilities (SDP) for sums of stationary Gaussian sequences. For the cases of constant boundaries and boundaries tending to zero, we obtain quite general results. For the case of the boundaries tending to…

Probability · Mathematics 2020-02-11 Frank Aurzada , Mikhail Lifshits
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