scispace - formally typeset
Open AccessJournal ArticleDOI

How sharp are classical approximations for statistical applications

TLDR
This paper aims at comparing theoretical approximations of the tail of the maximum of stochastic processes and the corresponding numerical evaluations of the Pickands or double sum method, the Rice Method, the Euler Characteristic method and a new one called the Poisson method.
Abstract
This paper aims at comparing theoretical approximations of the tail of the maximum of stochastic processes and the corresponding numerical evaluations. More particularly, we focus on the Pickands or double sum method, the Rice method, the Euler Characteristic method and a new one called the Poisson method. The numerical evaluation, performed using mainly Quasi Monte-Carlo integration and adaptations of the programs of Genz, show the domains of validity of each method.

read more

Content maybe subject to copyright    Report

Citations
More filters
Posted Content

Geometry of conjunction set of smooth stationary Gaussian fields

TL;DR: In this paper, the authors investigated the conjunction probability that at a same point the values of the Gaussian fields exceed the given threshold. And they gave a partial validity of Euler characteristic method, using a recent result of Azai s and Wschebor describing the shape of the excursion set.
Posted Content

Asymptotic formula for the conjunction probability of smooth stationary Gaussian fields

Viet-Hung Pham
- 16 Sep 2019 - 
TL;DR: In this paper, the authors derived an asymptotic formula for the conjunction probability of a stationary centered Gaussian field with smooth sample paths from the behavior of the volume of the set of local maximum points.
Journal ArticleDOI

Asymptotic formula for the conjunction probability of smooth stationary Gaussian fields

TL;DR: In this article , the authors derived an asymptotic formula for the conjunction probability of a stationary centered Gaussian field with smooth sample paths from the behavior of the volume of the set of local maximum points.
References
More filters
Book

Statistics for spatial data

TL;DR: In this paper, the authors present a survey of statistics for spatial data in the field of geostatistics, including spatial point patterns and point patterns modeling objects, using Lattice Data and spatial models on lattices.
Journal ArticleDOI

Mathematical analysis of random noise

TL;DR: In this paper, the authors used the representations of the noise currents given in Section 2.8 to derive some statistical properties of I(t) and its zeros and maxima.
Book

The Geometry of Random Fields

TL;DR: In this article, the authors present a survey of random fields and excursion sets and their spectral properties, including sample function regularity, sample function erraticism, and the Markov property for Gaussian fields.
Related Papers (5)