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We consider a system of $N$ Hawkes processes and observe the actions of a subpopulation of size $K \le N$ up to time $t$, where $K$ is large. The influence relationships between each pair of individuals are modeled by i.i.d.Bernoulli($p$)…

Probability · Mathematics 2026-01-06 Chenguang Liu , Liping Xu , An Zhang

We observe the actions of a $K$ sub-sample of $N$ individuals up to time $t$ for some large $K<N$. We model the relationships of individuals by i.i.d. Bernoulli($p$)-random variables, where $p\in (0,1]$ is an unknown parameter. The rate of…

Statistics Theory · Mathematics 2020-04-15 Chenguang Liu

We consider a population of $N$ individuals, of which we observe the number of actions as time evolves. For each couple of individuals $(i,j)$, $j$ may or not influence $i$, which we model by i.i.d. Bernoulli$(p)$-random variables, for some…

Statistics Theory · Mathematics 2016-01-28 Sylvain Delattre , Nicolas Fournier

We define the local empirical process, based on $n$ i.i.d. random vectors in dimension $d$, in the neighborhood of the boundary of a fixed set. Under natural conditions on the shrinking neighborhood, we show that, for these local empirical…

Statistics Theory · Mathematics 2011-04-22 John H. J. Einmahl , Estáte V. Khmaladze

This paper is concerned with statistical inference for infinite range interaction Gibbs point processes and in particular for the large class of Ruelle superstable and lower regular pairwise interaction models. We extend classical…

Statistics Theory · Mathematics 2015-10-05 Jean-François Coeurjolly , Frédéric Lavancier

In this work, a generalised version of the central limit theorem is proposed for nonlinear functionals of the empirical measure of i.i.d. random variables, provided that the functional satisfies some regularity assumptions for the…

Probability · Mathematics 2021-12-07 Benjamin Jourdain , Alvin Tse

We prove a central limit theorem for a sequence of random variables whose means are ambiguous and vary in an unstructured way. Their joint distribution is described by a set of measures. The limit is (not the normal distribution and is)…

Probability · Mathematics 2020-07-01 Zengjing Chen , Larry G. Epstein

Special case of a Gibbsian facet process on a fixed window with a discrete orientation distribution and with increasing intensity of the underlying Poisson process is studied. All asymptotic moments for interaction U-statistics are…

Probability · Mathematics 2015-10-06 Jakub Vecera

A finite range interacting particle system on a transitive graph is considered. Assuming that the dynamics and the initial measure are invariant, the normalized empirical distribution process converges in distribution to a centered…

Mathematical Physics · Physics 2007-05-23 Paul Doukhan , Gabriel Lang , Sana Louhichi , Bernard Ycart

We introduce and show the existence of a Hawkes self-exciting point process with exponentially-decreasing kernel and where parameters are time-varying. The quantity of interest is defined as the integrated parameter…

Statistical Finance · Quantitative Finance 2017-06-28 Simon Clinet , Yoann Potiron

The propagation of chaos and associated law of large numbers for mean-field interacting age-dependent Hawkes processes (when the number of processes n goes to +$\infty$) being granted by the study performed in (Chevallier, 2015), the aim of…

Probability · Mathematics 2016-11-08 Julien Chevallier

In this article, we study an interacting particle system in the context of epidemiology where the individuals (particles) are characterized by their position and infection state. We begin with a description at the microscopic level where…

Probability · Mathematics 2022-12-06 Maxime Hauray , Etienne Pardoux , Yen V. Vuong

We generalize multivariate Hawkes processes mainly by including a dependence with respect to the age of the process, i.e. the delay since the last point. Within this class, we investigate the limit behaviour, when n goes to infinity, of a…

Probability · Mathematics 2017-03-16 Julien Chevallier

Hawkes process is a self-exciting point process with clustering effect whose intensity depends on its entire past history. It has wide applications in neuroscience, finance and many other fields. In this paper, we obtain a functional…

Probability · Mathematics 2014-10-16 Lingjiong Zhu

We investigate here the behaviour of a large typical meandric system, proving a central limit theorem for the number of components of given shape. Our main tool is a theorem of Gao and Wormald, that allows us to deduce a central limit…

Probability · Mathematics 2024-11-20 Svante Janson , Paul Thévenin

In settings where interference between units is possible, we define the prevalence of indirect effects to be the number of units who are affected by the treatment of others. This quantity does not fully identify an indirect effect, but may…

Methodology · Statistics 2024-01-18 David Choi

A univariate Hawkes process is a simple point process that is self-exciting and has clustering effect. The intensity of this point process is given by the sum of a baseline intensity and another term that depends on the entire past history…

Probability · Mathematics 2018-10-04 Xuefeng Gao , Lingjiong Zhu

Consider a supercritical Crump-Mode-Jagers process $(\mathcal{Z}_{t}^{\varphi})_{t \geq 0}$ counted with a random characteristic $\varphi$ that depends on an individual's life and their descendant process up to a fixed generation. Under…

Probability · Mathematics 2025-11-25 Gabriel Berzunza Ojeda , Harlan Connor

In this paper we consider a sequence of random variables with mean uncertainty in a sublinear expectation space. Without the hypothesis of identical distributions, we show a new central limit theorem under the sublinear expectations.

Probability · Mathematics 2015-05-19 Min Li , Yufeng Shi

Interval-censored data solely records the aggregated counts of events during specific time intervals - such as the number of patients admitted to the hospital or the volume of vehicles passing traffic loop detectors - and not the exact…

Machine Learning · Computer Science 2022-11-29 Marian-Andrei Rizoiu , Alexander Soen , Shidi Li , Pio Calderon , Leanne Dong , Aditya Krishna Menon , Lexing Xie
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