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New results on uniform convergence in probability for expansions of Gaussian random processes using compactly supported wavelets are given. The main result is valid for general classes of nonstationary processes. An application of the…

Probability · Mathematics 2013-08-08 Yuriy Kozachenko , Andriy Olenko , Olga Polosmak

Let $\{X_i(t):\, t\in S\subset \R^d \}_{i=1,2,\ldots,n}$ be independent copies of a stationary centered Gaussian field with almost surely smooth sample paths. In this paper, we are interested in the conjunction probability defined as $\PP…

Probability · Mathematics 2020-09-07 Viet-Hung Pham

New results on uniform convergence in probability for the most general classes of wavelet expansions of stationary Gaussian random processes are given.

Probability · Mathematics 2013-07-10 Yuriy Kozachenko , Andriy Olenko , Olga Polosmak

We derive explicit lower and upper bounds for the probability generating functional of a stationary locally stable Gibbs point process, which can be applied to summary statistics like the F function. For pairwise interaction processes we…

Probability · Mathematics 2013-04-18 Kaspar Stucki , Dominic Schuhmacher

The paper characterizes uniform convergence rate for general classes of wavelet expansions of stationary Gaussian random processes. The convergence in probability is considered.

Probability · Mathematics 2013-08-08 Andriy Olenko , Yuriy Kozachenko , Olga Polosmak

Gaussian random fields on finite dimensional smooth manifolds whose variances reach their maximum value at smooth submanifolds are considered. Exact asymptotic behaviors of large excursion probabilities have been evaluated. Vector Gaussian…

Probability · Mathematics 2021-08-18 Vladimir I. Piterbarg

We study the accuracy of the expected Euler characteristic approximation to the distribution of the maximum of a smooth, centered, unit variance Gaussian process f. Using a point process representation of the error, valid for arbitrary…

Probability · Mathematics 2007-05-23 Jonathan Taylor , Akimichi Takemura , Robert J. Adler

Let $\{X_i(t),t\ge0\}, 1\le i\le n$ be independent centered stationary Gaussian processes with unit variance and almost surely continuous sample paths. For given positive constants $u,T$, define the set of conjunctions $C_{[0,T],u}:=\{t\in…

Probability · Mathematics 2014-10-08 Krzysztof Dȩbicki , Enkelejd Hashorva , Lanpeng Ji , Kamil Tabis

The convergence of a sequence of point processes with dependent points, defined by a symmetric function of iid high-dimensional random vectors, to a Poisson random measure is proved. This also implies the convergence of the joint…

Probability · Mathematics 2024-02-14 Johannes Heiny , Carolin Kleemann

In this paper, we derive an explicit upper bound for the Wasserstein distance between a functional of point processes and a Gaussian distribution. Using Stein's method in conjunction with Malliavin's calculus and the Poisson embedding…

Probability · Mathematics 2025-06-09 Laure Coutin , Benjamin Massat , Anthony Réveillac

Lower bounds for persistence probabilities of stationary Gaussian processes in discrete time are obtained under various conditions on the spectral measure of the process. Examples are given to show that the persistence probability can decay…

Probability · Mathematics 2016-02-02 Krishna M. , Manjunath Krishnapur

We study boundary non-crossing probabilities $$ P_{f,u} := \mathrm P\big(\forall t\in \mathbb T\ X_t + f(t)\le u(t)\big) $$ for continuous centered Gaussian process $X$ indexed by some arbitrary compact separable metric space $\mathbb T$.…

Probability · Mathematics 2020-03-16 Enkelejd Hashorva , Yuliya Mishura , Georgiy Shevchenko

We consider the Gaussian approximation for functionals of a Poisson process that are expressible as sums of region-stabilizing (determined by the points of the process within some specified regions) score functions and provide a bound on…

Probability · Mathematics 2022-09-20 Chinmoy Bhattacharjee , Ilya Molchanov

In this paper we study approximations for boundary crossing probabilities for the moving sums of i.i.d. normal random variables. We propose approximating a discrete time problem with a continuous time problem allowing us to apply developed…

Statistics Theory · Mathematics 2019-04-30 Jack Noonan , Anatoly Zhigljavsky

Due to their conjugate posteriors, Gaussian process priors are attractive for estimating the drift of stochastic differential equations with continuous time observations. However, their performance strongly depends on the choice of the…

Statistics Theory · Mathematics 2020-02-04 Jan van Waaij

Let $X= \{X(p), p\in M\}$ be a centered Gaussian random field, where $M$ is a smooth Riemannian manifold. For a suitable compact subset $D\subset M$, we obtain the approximations to excursion probability $\mathbb{P}\{\sup_{p\in D} X(p) \ge…

Probability · Mathematics 2015-05-05 Dan Cheng

Consider the point process (in $\mathbb{R}^d$) of local maxima of smooth Gaussian fields, with sufficient decay of correlation at infinity, above a level $u$. We show that this point process, rescaled appropriately, converges weakly to a…

Probability · Mathematics 2026-02-25 Dmitry Beliaev , Akshay Hegde

We study the largest gaps between successive zeros of a smooth stationary Gaussian process. Our main result is that, if correlations decay at least polynomially, then after suitable rescaling of the locations and sizes of the largest gaps…

Probability · Mathematics 2026-05-22 Renjie Feng , Stephen Muirhead

The evaluation of the probability of union of a large number of independent events requires several combinations involving the factorial and the use of high performance computers with several hours of processing. Bounds and simplifications…

Numerical Analysis · Mathematics 2025-03-07 Edson Luiz Ursini , Paulo S. Martins

In this paper, we give sufficient conditions to establish central limit theorems for boundary estimates of Poisson point processes. The considered estimates are obtained by smoothing some bias corrected extreme values of the point process.…

Statistics Theory · Mathematics 2011-03-31 Stéphane Girard , Ludovic Menneteau
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