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We address the counting of level crossings for inertial stochastic processes. We review Rice's approach to the problem and generalize the classical Rice formula to include all Gaussian processes in their most general form. We apply the…

Statistical Mechanics · Physics 2023-02-22 Jaume Masoliver , Matteo Palassini

Understanding the statistics of level crossings in stochastic processes is crucial across many scientific disciplines. The traditional Kac-Rice formula gives the mean rate of level crossings and has found broad use. However, that mean rate…

Probability · Mathematics 2026-05-26 Shivang Rawat , Flaviano Morone , David J. Heeger , Stefano Martiniani

We prove the asymptotic normality of the standardized number of crossings of a centered stationary mixing Gaussian process when both the level and the time horizon go to infinity in such a way that the expected number of crossings also goes…

Probability · Mathematics 2018-02-23 Federico Dalmao , José Rafael León , Ernesto Mordecki , Stéphane Mourareau

Graph-based methods for signal processing have shown promise for the analysis of data exhibiting irregular structure, such as those found in social, transportation, and sensor networks. Yet, though these systems are often dynamic,…

Machine Learning · Computer Science 2016-06-23 Nathanael Perraudin , Andreas Loukas , Francesco Grassi , Pierre Vandergheynst

This paper is an overview of the classical level crossing problem which is studied extensively in the literature and is fundamental in many branches of applied probability. We discuss a number of approximations with an emphasis on their…

Probability · Mathematics 2018-03-28 Vsevolod Malinovskii

The aim of this study is to extend the scope and applicability of the level-crossing method to discrete-time stochastic processes and generalize it to enable us to study multiple discrete-time stochastic processes. In previous versions of…

Data Analysis, Statistics and Probability · Physics 2016-09-15 Tayeb Jamali , G. R. Jafari , S. Vasheghani Farahani

We consider the persistence probability, the occupation-time distribution and the distribution of the number of zero crossings for discrete or (equivalently) discretely sampled Gaussian Stationary Processes (GSPs) of zero mean. We first…

Statistical Mechanics · Physics 2009-11-10 George M. C. A. Ehrhardt , Satya N. Majumdar , Alan J. Bray

In this article, we primarily propose a novel Bayesian characterization of stationary and nonstationary stochastic processes. In practice, this theory aims to distinguish between global stationarity and nonstationarity for both parametric…

Statistics Theory · Mathematics 2020-05-04 Sucharita Roy , Sourabh Bhattacharya

Let $X=\{X_t: t\ge 0\}$ be a stationary piecewise continuous $\R^d$-valued process that moves between jumps along the integral curves of a given continuous vector field, and let $S\subset\R^d$ be a smooth surface. The aim of this paper is…

Probability · Mathematics 2010-09-21 K. A. Borovkov , G. Last

We review the properties of time intervals between the crossings at a level M of a smooth stationary Gaussian temporal signal. The distribution of these intervals and the persistence are derived within the Independent Interval Approximation…

Statistical Mechanics · Physics 2008-07-24 Clément Sire

The chaos expansion of a general non-linear function of a Gaussian stationary increment process conditioned on its past realizations is derived. This work combines Wiener chaos expansion approach to study the dynamics of a stochastic system…

Probability · Mathematics 2018-04-12 Daniel Alpay , Alon Kipnis

Modelling spatio-temporal processes has become an important issue in current research. Since Gaussian processes are essentially determined by their second order structure, broad classes of covariance functions are of interest. Here, a new…

Statistics Theory · Mathematics 2011-02-28 Martin Schlather

This paper deals with Poisson processes on an arbitrary measurable space. Using a direct approach, we derive formulae for moments and cumulants of a vector of multiple Wiener-It\^o integrals with respect to the compensated Poisson process.…

Probability · Mathematics 2014-07-08 Guenter Last , Mathew D. Penrose , Matthias Schulte , Christoph Thaele

The seminal papers of Pickands [1,2] paved the way for a systematic study of high exceedance probabilities of both stationary and non-stationary Gaussian processes. Yet, in the vector-valued setting, due to the lack of key tools including…

Probability · Mathematics 2019-11-18 Krzysztof Dȩbicki , Enkelejd Hashorva , Longmin Wang

We extend Rice Formula to a process which is the sum of two independent processes: a smooth process and a pure jump process with finitely many jumps. Formulas for the mean number of both continuous and discontinuous crossings through a…

Probability · Mathematics 2015-02-09 Federico Dalmao , Ernesto Mordecki

We present a class of Gauss-Markov processes which can be represented as space-time scaled stationary Ornstein-Uhlenbeck processes defined on the real line. We give several explicit examples of the representation for certain Gauss bridge…

Probability · Mathematics 2019-01-28 Matyas Barczy , Peter Kern

In this paper, we present a new approach to derive series expansions for some Gaussian processes based on harmonic analysis of their covariance function. In particular, we propose a new simple rate-optimal series expansion for fractional…

Probability · Mathematics 2020-12-11 M. Ndaoud

This work is to popularize the method of computing the distribution of the excursion times for a Gaussian process that involves extended and multivariate Rice's formula. The approach was used in numerical implementations of the…

Probability · Mathematics 2020-07-29 Georg Lindgren , Krzysztof Podgorski , Igor Rychlik

We combine the method of exchangeable pairs with Stein's method for functional approximation. As a result, we give a general linearity condition under which an abstract Gaussian approximation theorem for stochastic processes holds. We apply…

Probability · Mathematics 2020-10-22 Mikolaj J. Kasprzak

The problem of (pathwise) large deviations for conditionally continuous Gaussian processes is investigated. The theory of large deviations for Gaussian processes is extended to the wider class of random processes -- the conditionally…

Probability · Mathematics 2019-02-07 Barbara Pacchiarotti , Alessandro Pigliacelli
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