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The occurrence of extreme events like heavy precipitation or storms at a certain location often shows a clustering behaviour and is thus not described well by a Poisson process. We construct a general model for the inter-exceedance times in…

Methodology · Statistics 2025-09-16 Christina Mathieu , Katharina Hees , Roland Fried

The extremal index $\theta$, a number in the interval $[0,1]$, is known to be a measure of primal importance for analyzing the extremes of a stationary time series. New rank-based estimators for $\theta$ are proposed which rely on the…

Statistics Theory · Mathematics 2020-06-30 Axel Bücher , Tobias Jennessen

Feature selection procedures for spatial point processes parametric intensity estimation have been recently developed since more and more applications involve a large number of covariates. In this paper, we investigate the setting where the…

Methodology · Statistics 2017-12-29 Achmad Choiruddin , Jean-François Coeurjolly , Frédérique Letué

We consider a piecewise-deterministic Markov process governed by a jump intensity function, a rate function that determines the behaviour between jumps, and a stochastic kernel describing the conditional distribution of jump sizes. We study…

Probability · Mathematics 2010-09-22 K. A. Borovkov , G. Last

For arrays $(S_{i,j})_{1\leq i\leq j}$ of random variables that are stationary in an appropriate sense, we show that the fluctuations of the process $(S_{1,n})_{n=1}^{\infty}$ can be bounded in terms of a measure of the ``mean…

Dynamical Systems · Mathematics 2016-09-07 Michael Hochman

We consider disjoint and sliding blocks estimators of cluster indices for multivariate, regularly varying time series in the Peak-over-Threshold framework. We aim to provide a complete description of the limiting behaviour of these…

Statistics Theory · Mathematics 2023-09-07 Zaoli Chen , Rafał Kulik

We derive the limiting distributions of exceedances point processes of randomly scaled weakly dependent stationary Gaussian sequences under some mild asymptotic conditions. In the literature analogous results are available only for…

Probability · Mathematics 2013-10-22 Enkelejd Hashorva , Zuoxiang Peng , Zhichao Weng

In counting experiments, one can set an upper limit on the rate of a Poisson process based on a count of the number of events observed due to the process. In some experiments, one makes several counts of the number of events, using…

Data Analysis, Statistics and Probability · Physics 2014-11-20 Patrick J. Sutton

The Poisson process is the most elementary continuous-time stochastic process that models a stream of repeating events. It is uniquely characterised by a single parameter called the rate. Instead of a single value for this rate, we here…

Probability · Mathematics 2019-06-05 Alexander Erreygers , Jasper De Bock

The problem of finding the expected value of a statistic of a locally stable point process in a bounded region is addressed. We propose an adaptive importance sampling for solving the problem. In our proposal, we restrict the importance…

Machine Learning · Statistics 2025-03-04 Hee-Geon Kang , Sunggon Kim

This note aims at presenting several new theoretical results for the compound Poisson point process, which follows the work of Zhang \emph{et al.} [Insurance~Math.~Econom.~59(2014), 325-336]. The first part provides a new characterization…

Statistics Theory · Mathematics 2019-12-10 Huiming Zhang , Xiaoxu Wu

When there is no independence, abnormal observations may have a tendency to appear in clusters instead of scattered along the time frame. Identifying clusters and estimating their size are important problems arising in statistics of…

Probability · Mathematics 2020-01-08 Miguel Abadi , Ana Cristina Moreira Freitas , Jorge Milhazes Freitas

Let $\eta_t$ be a Poisson point process of intensity $t\geq 1$ on some state space $\Y$ and $f$ be a non-negative symmetric function on $\Y^k$ for some $k\geq 1$. Applying $f$ to all $k$-tuples of distinct points of $\eta_t$ generates a…

Probability · Mathematics 2012-12-11 Matthias Schulte , Christoph Thaele

In this paper we consider the problem of estimating the parameters of a Poisson arrival process where the rate function is assumed to lie in the span of a known basis. Our goal is to estimate the basis expansions coefficients given a…

Information Theory · Computer Science 2018-12-24 Michael G. Moore , Mark A. Davenport

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

A class of improved estimators is proposed for N-point correlation functions of galaxy clustering, and for discrete spatial random processes in general. In the limit of weak clustering, the variance of the unbiased estimator converges to…

Astrophysics · Physics 2007-05-23 István Szapudi , Alexander S. Szalay

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

This paper studies the critical and near-critical regimes of the planar random-cluster model on $\mathbb Z^2$ with cluster-weight $q\in[1,4]$ using novel coupling techniques. More precisely, we derive the scaling relations between the…

Probability · Mathematics 2020-12-01 Hugo Duminil-Copin , Ioan Manolescu

In extreme value statistics for stationary sequences, blocks estimators are usually constructed by using disjoint blocks because exceedances over high thresholds of different blocks can be assumed asymptotically independent. In this paper…

Statistics Theory · Mathematics 2008-12-23 Christian Y. Robert , Johan Segers , Christopher A. T. Ferro

Consider the max-stable process $\eta(t) = \max_{i\in\mathbb N} U_i \rm{e}^{\langle X_i, t\rangle - \kappa(t)}$, $t\in\mathbb{R}^d$, where $\{U_i, i\in\mathbb{N}\}$ are points of the Poisson process with intensity $u^{-2}\rm{d} u$ on…

Probability · Mathematics 2015-12-09 Sebastian Engelke , Zakhar Kabluchko