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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

In this paper we consider point processes specified on directed linear networks, i.e. linear networks with associated directions. We adapt the so-called conditional intensity function used for specifying point processes on the time line to…

Statistics Theory · Mathematics 2019-01-03 Jakob G. Rasmussen , Heidi S. Christensen

We explore the concept of memory in scalar active matter, focusing on the collective dynamics of particles whose interactions depend on their evolutionary history rather than solely on their current configuration. We introduce the idea of…

Soft Condensed Matter · Physics 2026-03-25 Vaishnavi Gajendragad , Suropriya Saha

We characterize a Hawkes point process with kernel proportional to the probability density function of Mittag-Leffler random variables. This kernel decays as a power law with exponent $\beta +1 \in (1,2]$. Several analytical results can be…

For a Pfaffian point process we show that its Palm measures, its normalised compositions with multiplicative functionals, and its conditional measures with respect to fixing the configuration in a bounded subset are Pfaffian point processes…

Probability · Mathematics 2019-12-24 Alexander I. Bufetov , Fabio Deelan Cunden , Yanqi Qiu

In this article, we primarily propose a novel Bayesian characterization of stationary and nonstationary stochastic processes. In practice, this theory aims to distinguish between global stationarity and nonstationarity for both parametric…

Statistics Theory · Mathematics 2020-05-04 Sucharita Roy , Sourabh Bhattacharya

The tail process $\boldsymbol{Y}=(Y_{\boldsymbol{i}})_{\boldsymbol{i}\in\mathbb{Z}^d}$ of a stationary regularly varying random field $\boldsymbol{X}=(X_{\boldsymbol{i}})_{\boldsymbol{i}\in\mathbb{Z}^d}$ represents the asymptotic local…

Probability · Mathematics 2023-03-15 Hrvoje Planinić

In this paper we consider some non linear Hawkes processes with signed reproduction function (or memory kernel) thus exhibiting both self-excitation and inhibition. We provide a Law of Large Numbers, a Central Limit Theorem and large…

Probability · Mathematics 2022-07-06 Patrick Cattiaux , Laetitia Colombani , Manon Costa

In this paper, we use the Hawkes process to model the sequence of failure, i.e., events of compressor station and conduct survival analysis on various failure events of the compressor station. However, until now, nearly all relevant…

Machine Learning · Computer Science 2021-12-28 Lu-ning Zhang , Jian-wei Liu , Xin Zuo

We study the mutual regularity properties of Palm measures of point processes, and establish that a key determining factor for these properties is the rigidity-tolerance behaviour of the point process in question (for those processes that…

Probability · Mathematics 2016-11-23 Subhro Ghosh

Student procrastination and cramming for deadlines are major challenges in online learning environments, with negative educational and well-being side effects. Modeling student activities in continuous time and predicting their next study…

Machine Learning · Computer Science 2021-02-02 Mengfan Yao , Siqian Zhao , Shaghayegh Sahebi , Reza Feyzi Behnagh

* ACTIVATED RANDOM WALK MODEL * This is a conservative particle system on the lattice, with a Markovian continuous-time evolution. Active particles perform random walks without interaction, and they may as well change their state to…

Probability · Mathematics 2011-03-15 Leonardo T. Rolla

The main result of this note is that the shift of the parameter by 1 in the parameter space of decomposing measures in the problem of harmonic analysis on the infinite-dimensional unitary group corresponds to the taking of the reduced Palm…

Probability · Mathematics 2024-01-02 Alexander I. Bufetov

We introduce a point process regression model that is applicable to price models and limit order book models. Hawkes type autoregression in the intensity process is generalized to a stochastic regression to covariate processes. We establish…

Statistics Theory · Mathematics 2015-12-08 Teppei Ogihara , Nakahiro Yoshida

Both Hawkes processes and autoregressive processes rely on linear functionals of their past, while modeling different types of data. Since datasets arising from observations of the same phenomenon may be heterogeneous and sampled at…

Probability · Mathematics 2026-05-28 Théo Leblanc

In this work, we propose to catch the complexity of the membrane potential's dynamic of a motoneuron between its spikes, taking into account the spikes from other neurons around. Our approach relies on two types of data: extracellular…

Statistics Theory · Mathematics 2021-08-03 Anna Bonnet , Charlotte Dion , François Gindraud , Sarah Lemler

Via operator theoretic methods, we formalize the concentration phenomenon for a given observable `$r$' of a discrete time Markov chain with `$\mu_{\pi}$' as invariant ergodic measure, possibly having support on an unbounded state space. The…

Machine Learning · Computer Science 2023-06-01 Muhammad Abdullah Naeem , Miroslav Pajic

Let $X$ be a locally compact Polish space and $\sigma$ a nonatomic reference measure on $X$ (typically $X=\mathbb R^d$ and $\sigma$ is the Lebesgue measure). Let $X^2\ni(x,y)\mapsto\mathbb K(x,y)\in\mathbb C^{2\times 2}$ be a $2\times…

Probability · Mathematics 2022-08-24 Maryam Gharamah Ali Alshehri , Eugene Lytvynov

Small-space and large-time estimates and asymptotic expansion of the distribution function and (the derivatives of) the density function of hitting times of points for symmetric L\'evy processes are studied. The L\'evy measure is assumed to…

Probability · Mathematics 2017-02-15 Tomasz Juszczyszyn , Mateusz Kwaśnicki

We analyze a non-Markovian mean field interacting spin system, related to the Curie--Weiss model. We relax the Markovianity assumption by replacing the memoryless distribution of the waiting times of a classical spin-flip dynamics with a…

Probability · Mathematics 2019-11-14 Paolo Dai Pra , Marco Formentin , Guglielmo Pelino