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We obtain asymptotic approximations for the probability density function of the product of two correlated normal random variables with non-zero means and arbitrary variances. As a consequence, we deduce asymptotic approximations for the…

Probability · Mathematics 2024-10-22 Robert E. Gaunt , Zixin Ye

In this paper, we derive tail approximations of integrals of exponential functions of Gaussian random fields with varying mean functions and approximations of the associated point processes. This study is motivated naturally by multiple…

Statistics Theory · Mathematics 2011-12-05 Jingchen Liu , Gongjun Xu

We examine the width of the gamma-ray burst (GRB) luminosity function through the distribution of GRB peak count rates, C$_{\rm{peak}}$, as detected by BATSE (\cite{batse:93}). In the context of galactic corona spatial distribution models,…

Astrophysics · Physics 2009-10-22 Andrew Ulmer , Ralph A. M. J. Wijers

Consider a random sample in the max-domain of attraction of a multivariate extreme value distribution such that the dependence structure of the attractor belongs to a parametric model. A new estimator for the unknown parameter is defined as…

Statistics Theory · Mathematics 2012-10-05 John H. J. Einmahl , Andrea Krajina , Johan Segers

Riemann's non-differentiable function is a classic example of a continuous function which is almost nowhere differentiable, and many results concerning its analytic regularity have been shown so far. However, it can also be given a…

Classical Analysis and ODEs · Mathematics 2020-03-05 Daniel Eceizabarrena

In risk management, tail risks are of crucial importance. The assessment of risks should be carried out in accordance with the regulatory authority's requirement at high quantiles. In general, the underlying distribution function is…

Risk Management · Quantitative Finance 2020-07-15 Ingo Hoffmann , Christoph J. Börner

A spectral approach to Bayesian inference is presented. It pursues the emulation of the posterior probability density. The starting point is a series expansion of the likelihood function in terms of orthogonal polynomials. From this…

Computation · Statistics 2016-04-27 Joseph B. Nagel , Bruno Sudret

Understanding the shape of a distribution of data is of interest to people in a great variety of fields, as it may affect the types of algorithms used for that data. We study one such problem in the framework of distribution property…

Machine Learning · Computer Science 2022-12-06 Maryam Aliakbarpour , Amartya Shankha Biswas , Kavya Ravichandran , Ronitt Rubinfeld

The visibility algorithm has been recently introduced as a mapping between time series and complex networks. This procedure allows to apply methods of complex network theory for characterizing time series. In this work we present the…

Data Analysis, Statistics and Probability · Physics 2010-02-25 Bartolo Luque , Lucas Lacasa , Fernando Ballesteros , Jordi Luque

We formulate and study a model for inhomogeneous long-range percolation on $\Zbold^d$. Each vertex $x\in\Zbold^d$ is assigned a non-negative weight $W_x$, where $(W_x)_{x\in\Zbold^d}$ are i.i.d.\ random variables. Conditionally on the…

Probability · Mathematics 2011-03-02 Maria Deijfen , Remco van der Hofstad , Gerard Hooghiemstra

The object of study is a soft random geometric graph with vertices given by a Poisson point process on a line and edges between vertices present with probability that has a polynomial decay in the distance between them. Various aspects of…

Probability · Mathematics 2023-11-21 Arnaud Rousselle , Ercan Sönmez

Let G(V,E) be a simple graph and let X subset of V. Two vertices u and v are said to be X-visible if there exists a shortest u,v-path P such that V(P) intersection X is a subset of {u, v}. A set X is called a mutual-visibility set of G if…

Combinatorics · Mathematics 2026-04-10 Tonny K B , Shikhi M

We consider the Gumbel or extreme value statistics describing the distribution function p_G(x_max) of the maximum values of a random field x within patches of fixed size. We present, for smooth Gaussian random fields in two and three…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-27 S. Colombi , O. Davis , J. Devriendt , S. Prunet , J. Silk

In a recent article the authors obtained a formula which relates explicitly the tail of risk neutral returns with the wing behavior of the Black Scholes implied volatility smile. In situations where precise tail asymptotics are unknown but…

Probability · Mathematics 2007-05-23 Shalom Benaim , Peter Friz

We have done a statistical analysis of some properties of the contour lines Im$(\zeta (s))$ = 0 of the Riemann zeta function. We find that this function is broken up into strips whose average width on the critical line does not appear to…

Number Theory · Mathematics 2012-10-16 Ronald Fisch

We introduce a general approach to traces that we consider as linear continuous functionals on some function space where we focus on some special choices for that space. This leads to an integral calculus for the computation of the precise…

Analysis of PDEs · Mathematics 2025-10-28 Moritz Schönherr , Friedemann Schuricht

We compute the tail asymptotics of the product of a beta random variable and a generalized gamma random variable which are independent and have general parameters. A special case of these asymptotics were proved and used in a recent work of…

Probability · Mathematics 2015-09-10 Jim Pitman , Miklos Z. Racz

With the present and soon-to-be breakthrough of optical interferometry, countless objects shall be within reach of interferometers; yet, most of them are expected to remain only marginally resolved with hectometric baselines. In this paper,…

Astrophysics · Physics 2009-11-07 Regis Lachaume

The Rosenfeld functional provides excellent results for the prediction of the fluid phase of hard convex particle systems but fails beyond the freezing point. The reason for this limitation is the neglect of orientational and distance…

Statistical Mechanics · Physics 2012-08-21 Stephan Korden

This article describes a multivariate polynomial regression method where the uncertainty of the input parameters are approximated with Gaussian distributions, derived from the central limit theorem for large weighted sums, directly from the…

Machine Learning · Statistics 2013-10-04 Peter Kovesarki , Ian C. Brock