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A compound Poisson process whose parameters are all unknown is observed at finitely many equispaced times. Nonparametric estimators of the jump and L\'evy distributions are proposed and functional central limit theorems using the uniform…

Statistics Theory · Mathematics 2017-02-06 Alberto J. Coca

We consider percolation properties of the Boolean model generated by a Gibbs point process and balls with deterministic radius. We show that for a large class of Gibbs point processes there exists a critical activity, such that percolation…

Probability · Mathematics 2013-08-12 Kaspar Stucki

We study positive random variables whose moments can be expressed by products and quotients of Gamma functions; this includes many standard distributions. General results are given on existence, series expansion and asymptotics of density…

Probability · Mathematics 2010-02-23 Svante Janson

The inspection of residuals is a fundamental step to investigate the quality of adjustment of a parametric model to data. For spatial point processes, the concept of residuals has been recently proposed by Baddeley et al. (2005) as an…

Statistics Theory · Mathematics 2013-08-07 Jean-François Coeurjolly , Frédéric Lavancier

It is well known that upward conditioned Brownian motion is a three-dimensional Bessel process, and that a downward conditioned Bessel process is a Brownian motion. We give a simple proof for this result, which generalizes to any continuous…

Probability · Mathematics 2012-10-10 Nicolas Perkowski , Johannes Ruf

When each site of a spatially extended excitable medium is independently driven by a Poisson stimulus with rate h, the interplay between creation and annihilation of excitable waves leads to an average activity F. It has recently been…

Neurons and Cognition · Quantitative Biology 2008-05-22 Tiago L. Ribeiro , Mauro Copelli

In this paper we consider the persistence properties of random processes in Brownian scenery, which are examples of non-Markovian and non-Gaussian processes. More precisely we study the asymptotic behaviour for large $T$, of the probability…

Probability · Mathematics 2015-02-25 Fabienne Castell , Nadine Guillotin-Plantard , Frederique Watbled

We extend results on time-rescaled occupation time fluctuation limits of the $(d,\alpha, \beta)$-branching particle system $(0<\alpha \leq 2, 0<\beta \leq 1)$ with Poisson initial condition. The earlier results in the homogeneous case…

Probability · Mathematics 2012-03-14 Tomasz Bojdecki , Luis G. Gorostiza , Anna Talarczyk

We analyze circumstances under which the microscopic dynamics of particles which are driven by a forced, gradient-type flow can be consistently interpreted as a Markovian diffusion process. Special attention is paid to discriminating…

Condensed Matter · Physics 2007-05-23 P. Garbaczewski

Gorini-Kossakowski-Sudarshan-Lindblad equation of Poisson-type for the density matrix is considered. The Poisson jumps are assumed to be unitary operators with generators, which are quadratic in fermionic creation and annihilation…

Quantum Physics · Physics 2021-05-11 Iu. A. Nosal , A. E. Teretenkov

We provide a sufficient condition for the uniqueness in distribution of Gibbs point processes with non-negative pairwise interaction, together with convergent expansions of the log-Laplace functional, factorial moment densities and…

Probability · Mathematics 2020-01-14 Sabine Jansen

Compared to the conditional mean as a simple point estimator, the conditional density function is more informative to describe the distributions with multi-modality, asymmetry or heteroskedasticity. In this paper, we propose a novel…

Methodology · Statistics 2020-10-22 Yiping Guo , Howard D. Bondell

We derive an exact probabilistic representation for the evolution of a Hubbard model with site- and spin-dependent hopping coefficients and site-dependent interactions in terms of an associated stochastic dynamics of a collection of Poisson…

We consider a multidimensional time-homogeneous dynamical system and add a randomly perturbed time-dependent deterministic signal to some of its components, giving rise to a high-dimensional system of stochastic differential equations,…

Probability · Mathematics 2019-08-02 Simon Holbach

Gibbsian structure in random point fields has been a classical tool for studying their spatial properties. However, exact Gibbs property is available only in a relatively limited class of models, and it does not adequately address many…

Probability · Mathematics 2023-05-26 Ujan Gangopadhyay , Subhro Ghosh , Kin Aun Tan

We study the problem of non-parametric Bayesian estimation of the intensity function of a Poisson point process. The observations are $n$ independent realisations of a Poisson point process on the interval $[0,T]$. We propose two related…

Methodology · Statistics 2020-03-31 Shota Gugushvili , Frank van der Meulen , Moritz Schauer , Peter Spreij

Poisson processes and one-dimensional Poisson point processes satisfy three main properties: superposition, thinning, and conditioning. The proof of the first two relies on basic estimates involving the Poisson distribution that are also…

Probability · Mathematics 2025-09-01 Nicolas Lanchier

We consider two-dimensional marked point processes which are Gibbsian with a two-body-potential U. U is supposed to have an internal continuous symmetry. We show that under suitable continuity conditions the considered processes are…

Probability · Mathematics 2007-05-23 Thomas Richthammer

We study deterministic systems, composed of excitable units of FitzHugh-Nagumo type, that are capable of self-generating and self-terminating strong deviations from their regular dynamics without the influence of noise or parameter change.…

Chaotic Dynamics · Physics 2014-08-28 Gerrit Ansmann , Rajat Karnatak , Klaus Lehnertz , Ulrike Feudel

Determinantal point processes on a measure space X whose kernels represent trace class Hermitian operators on L^2(X) are associated to "quasifree" density operators on the Fock space over L^2(X).

Probability · Mathematics 2007-05-23 Alex D. Gottlieb