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We study the probability distribution of the maximum $M_S $ of a smooth stationary Gaussian field defined on a fractal subset $S$ of $\R^n$. Our main result is the equivalent of the asymptotic behavior of the tail of the distribution…

Probability · Mathematics 2011-09-20 Jean-Marc Azaïs , Mario Wschebor

In this paper we present the distribution of the maximum of the asymmetric telegraph process in an arbitrary time interval $[0,t]$ under the conditions that the initial velocity $V(0)$ is either $c_1$ or $-c_2$ and the number of changes of…

Probability · Mathematics 2020-10-07 Fabrizio Cinque , Enzo Orsingher

We consider maximum likelihood estimation with data from a bivariate Gaussian process with a separable exponential covariance model under fixed domain asymptotic. We first characterize the equivalence of Gaussian measures under this model.…

Statistics Theory · Mathematics 2018-07-25 Daira Velandia , François Bachoc , Moreno Bevilacqua , Xavier Gendre , Jean-Michel Loubes

We investigate the asymptotic distribution of the maximum of a frequency smoothed estimate of the spectral coherence of a M-variate complex Gaussian time series with mutually independent components when the dimension M and the number of…

Statistics Theory · Mathematics 2021-07-08 Alexis Rosuel , Philippe Loubaton , Pascal Vallet

We consider a one-dimensional stationary stochastic process $x(\tau)$ of duration $T$. We study the probability density function (PDF) $P(t_{\rm m}|T)$ of the time $t_{\rm m}$ at which $x(\tau)$ reaches its global maximum. By using a path…

Statistical Mechanics · Physics 2021-10-15 Francesco Mori , Satya N. Majumdar , Gregory Schehr

We consider a one-dimensional stationary time series of fixed duration $T$. We investigate the time $t_{\rm m}$ at which the process reaches the global maximum within the time interval $[0,T]$. By using a path-decomposition technique, we…

Statistical Mechanics · Physics 2022-11-23 Francesco Mori , Satya N. Majumdar , Gregory Schehr

We consider the problem of estimating a smooth functional of an unknown signal with discontinuity from Gaussian observations. The signal is a known function that depends on an unknown parameter. This problem is closely related to the famous…

Statistics Theory · Mathematics 2011-12-19 Farida Enikeeva

Let $\{f(t): t\in T\}$ be a smooth Gaussian random field over a parameter space $T$, where $T$ may be a subset of Euclidean space or, more generally, a Riemannian manifold. For any local maximum of $f(t)$ located at $t_0$ in the interior of…

Probability · Mathematics 2014-12-24 Dan Cheng , Armin Schwartzman

We study the persistence probability for some discrete-time, time-reversible processes. In particular, we deduce the persistence exponent in a number of examples: first, we deal with random walks in random sceneries (RWRS) in any dimension…

Probability · Mathematics 2015-02-25 Frank Aurzada , Nadine Guillotin-Plantard

Let $\{X(t):t\in[0,\infty)\}$ be a centered Gaussian process with stationary increments and variance function $\sigma^2_X(t)$. We study the exact asymptotics of ${\mathbb{P}}(\sup_{t\in[0,T]}X(t)>u)$ as $u\to\infty$, where $T$ is an…

Probability · Mathematics 2011-02-16 Marek Arendarczyk , Krzysztof Dȩbicki

Given a set of independent Poisson random variables with common mean, we study the distribution of their maximum and obtain an accurate asymptotic formula to locate the most probable value of the maximum. We verify our analytic results with…

Probability · Mathematics 2009-03-26 K. M. Briggs , L. Song , T. Prellberg

The purpose of the article is twofold. Firstly, we review some recent results on the maximum likelihood estimation in the regression model of the form $X_t = \theta G(t) + B_t$, where $B$ is a Gaussian process, $G(t)$ is a known function,…

Probability · Mathematics 2018-12-27 Yuliya Mishura , Kostiantyn Ralchenko , Sergiy Shklyar

Let $\{X_{n}(t), t\in[0,\infty)\}, n\in\mathbb{N}$ be a sequence of centered dependent stationary Gaussian processes. The limit distribution of $\sup_{t\in[0,T(n)]}|X_{n}(t)|$ is established as $r_{n}(t)$, the correlation function of…

Probability · Mathematics 2014-12-12 Z. Tan , E. Hashorva , Z. Peng

This article describes a robust algorithm to estimate a conditional probability density f(t|x) as a non-parametric smooth regression function. It is based on a neural network and the Bayesian interpretation of the network output as a…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Michael Feindt

Many inference problems involving questions of optimality ask for the maximum or the minimum of a finite set of unknown quantities. This technical report derives the first two posterior moments of the maximum of two correlated Gaussian…

Machine Learning · Statistics 2009-10-02 Philipp Hennig

We consider the rate of piecewise constant approximation to a locally stationary process $X(t),t\in [0,1]$, having a variable smoothness index $\alpha(t)$. Assuming that $\alpha(\cdot)$ attains its unique minimum at zero and satisfies the…

Probability · Mathematics 2015-11-19 Enkelejd Hashorva , Mikhail Lifshits , Oleg Seleznjev

Motivated by the problem of testing for the existence of a signal of known parametric structure and unknown ``location'' (as explained below) against a noisy background, we obtain for the maximum of a centered, smooth random field an…

Statistics Theory · Mathematics 2008-06-27 Yuval Nardi , David O. Siegmund , Benjamin Yakir

Let $\{X(t)= (X_1(t),X_2(t))^T,\ t \in \mathbb{R}^N\}$ be an $\mathbb{R}^2$-valued continuous locally stationary Gaussian random field with $\mathbb{E}[X(t)]=\mathbf{0}$. For any compact sets $A_1, A_2 \subset \mathbb{R}^N$, precise…

Probability · Mathematics 2015-11-13 Yuzhen Zhou , Yimin Xiao

Max-stable distributions and processes are important models for extreme events and the assessment of tail risks. The full, multivariate likelihood of a parametric max-stable distribution is complicated and only recent advances enable its…

Statistics Theory · Mathematics 2017-08-08 Clement Dombry , Sebastian Engelke , Marco Oesting

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
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