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The fractional non-homogeneous Poisson process was introduced by a time-change of the non-homogeneous Poisson process with the inverse $\alpha$-stable subordinator. We propose a similar definition for the (non-homogeneous) fractional…

Probability · Mathematics 2017-11-27 Nikolai Leonenko , Enrico Scalas , Mailan Trinh

The stochastic properties of a Langevin-type Markov process can be extracted from a given time series by a Markov analysis. Also processes that obey a stochastically forced second order differential equation can be analyzed this way by…

Data Analysis, Statistics and Probability · Physics 2014-12-09 Bernd Lehle , Joachim Peinke

Let $\eta_t$ be a Poisson point process with intensity measure $t\mu$, $t>0$, over a Borel space $\mathbb{X}$, where $\mu$ is a fixed measure. Another point process $\xi_t$ on the real line is constructed by applying a symmetric function…

Probability · Mathematics 2015-10-02 Matthias Schulte , Christoph Thaele

Point processes and, more generally, random measures are ubiquitous in modern statistics. However, they can only take positive values, which is a severe limitation in many situations. In this work, we introduce and study random signed…

Probability · Mathematics 2024-11-20 Riccardo Passeggeri

The stochastic theory of relativistic quantum mechanics presented here is modelled on the one that has been proposed previously and that was claimed to be a promising substitute to the orthodox theory in the non-relativistic domain. So it…

Quantum Physics · Physics 2020-06-09 Maurice Godart

Random processes with stationary increments and intrinsic random processes are two concepts commonly used to deal with non-stationary random processes. They are broader classes than stationary random processes and conceptually closely…

Probability · Mathematics 2025-12-05 Jongwook Kim

This paper is concerned with ergodic properties of inhomogeneous Markov processes. Since the transition probabilities depend on initial times, the existing methods to obtain invariant measures for homogeneous Markov processes are not…

Probability · Mathematics 2025-01-24 Zhenxin Liu , Di Lu

Particle theorists typically use expectation values to study the quantum back-reaction on inflation, whereas many cosmologists stress the stochastic nature of the process. While expectation values certainly give misleading results for some…

General Relativity and Quantum Cosmology · Physics 2014-11-21 N. C. Tsamis , Aggelos Tzetzias , R. P. Woodard

Piecewise Deterministic Markov Processes (PDMPs) are studied in a general framework. First, different constructions are proven to be equivalent. Second, we introduce a coupling between two PDMPs following the same differential flow which…

Probability · Mathematics 2021-08-03 Alain Durmus , Arnaud Guillin , Pierre Monmarché

Quantifying energy flows at nanometer scales promises to guide future research in a variety of disciplines, from microscopic control and manipulation, to autonomously operating molecular machines. A general understanding of the…

Statistical Mechanics · Physics 2018-11-26 Steven J. Large , Raphaël Chetrite , David A. Sivak

In a previous Letter (J. Phys. A v.47 (2014) 212003) we have presented numerical evidence that a Hamiltonian expressed in terms of the generators of the periodic Temperley-Lieb algebra has, in the finite-size scaling limit, a spectrum given…

Statistical Mechanics · Physics 2015-08-26 Francisco C. Alcaraz , Pavel Pyatov , Vladimir Rittenberg

An approach for the description of stochastic systems is derived. Some of the variables in the system are studied forward in time, others backward in time. The approach is based on a perturbation expansion in the strength of the coupling…

Statistical Mechanics · Physics 2021-08-04 Piero Olla

A Neyman-Scott process is a special case of a Cox process. The latent and observable stochastic processes are both Poisson processes. We consider a deep Neyman-Scott process in this paper, for which the building components of a network are…

Machine Learning · Statistics 2022-05-10 Chengkuan Hong , Christian R. Shelton

We study systems of simple point processes that admit stochastic intensities. We represent these point processes as thinnings of Poisson measures and are interested in a convergence result of such systems. This result states that, if the…

Probability · Mathematics 2021-05-11 Xavier Erny

Lecture notes for a master-level applied mathematics course on stochastic processes and applications, held at the University of Orl\'eans, France. Contents: Markov chains, Poisson point processes, Markovian jump processes, queueing theory.…

History and Overview · Mathematics 2013-12-31 Nils Berglund

This paper present a construction and the analysis of a class of non-Gaussian positive-definite matrix-valued homogeneous random fields with uncertain spectral measure for stochastic elliptic operators. Then the stochastic elliptic boundary…

Probability · Mathematics 2021-06-16 Christian Soize

The theory of monotonicity and duality is developed for general one-dimensional Feller processes. Moreover it is shown that local monotonicity conditions (conditions on the L\'evy kernel) are sufficient to prove the well-posedness of the…

Probability · Mathematics 2022-05-03 Vassili Kolokoltsov

We study ergodic properties of a family of traffic maps acting in the space of bi-infinite sequences of real numbers. The corresponding dynamics mimics the motion of vehicles in a simple traffic flow, which explains the name. Using…

Dynamical Systems · Mathematics 2015-06-11 Michael Blank

Several stochastic processes related to transient L\'evy processes with potential densities $u(x,y)=u(y-x)$, that need not be symmetric nor bounded on the diagonal, are defined and studied. They are real valued processes on a space of…

Probability · Mathematics 2013-11-11 Yves Le Jan , Michael B. Marcus , Jay Rosen

We introduce a simple but powerful technique to study processes driven by two or more reinforcement mechanisms in competition. We apply our method to two types of models: to non conservative zero range processes on finite graphs, and to…

Probability · Mathematics 2022-06-30 Dirk Erhard , Guilherme Reis
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