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A transformation group approach to the prior for the parameters of the beta distribution is suggested which accounts for finite sets of data by imposing a limit to the range of parameter values under consideration. The relationship between…

Data Analysis, Statistics and Probability · Physics 2016-10-18 Robert W. Johnson

Previously it has been shown that some classes of mixing dynamical systems have limiting return times distributions that are almost everywhere Poissonian. Here we study the behaviour of return times at periodic points and show that the…

Dynamical Systems · Mathematics 2014-03-04 N. Haydn , S. Vaienti

We consider one-dimensional and two-dimensional models of the stochastic resin transfer molding process, which are formulated as random moving boundary problems. We study their properties, analytically in the one-dimensional case and…

Fluid Dynamics · Physics 2019-04-03 M. Park , M. V. Tretyakov

This paper examines some probabilistic properties of the class of periodic GARCH processes (PGARCH) which feature periodicity in conditional heteroskedasticity. In these models, the parameters are allowed to switch between different…

Probability · Mathematics 2007-09-20 Abdelouahab Bibi , Abdelhakim Aknouche

In this paper we will describe a parallel between phenomenological and symmetry-based descriptions of the process dependence of the time-reversal-odd phenomena in QCD, such as the Sivers effect, with the goal of defining the essential…

High Energy Physics - Phenomenology · Physics 2021-07-30 Dylan Manna , Andrea Signori , Christine Aidala

We consider a class of stochastic dynamical systems, called piecewise deterministic Markov processes, with states $(x, \s)\in \O\times \G$, $\O$ being a region in $\bbR^d$ or the $d$--dimensional torus, $\G$ being a finite set. The…

Statistical Mechanics · Physics 2009-02-25 Alessandra Faggionato , Davide Gabrielli , Marco Ribezzi Crivellari

We present the formalism of sequential and asynchronous processes defined in terms of random or quantum grammars and argue that these processes have relevance in genomics. To make the article accessible to the non-mathematicians, we keep…

Probability · Mathematics 2007-05-23 Dimitri Petritis

In this paper we present some extensions of recent noncentral moderate deviation results in the literature. In the first part we generalize the results in \cite{BeghinMacciSPL2022} by considering a general L\'evy process $\{S(t):t\geq 0\}$…

Probability · Mathematics 2025-01-03 Antonella Iuliano , Claudio Macci , Alessandra Meoli

We study the existence of densities for distributions of piecewise deterministic Markov processes. We also obtain relationships between invariant densities of the continuous time process and that of the process observed at jump times. In…

Probability · Mathematics 2020-06-03 Piotr Gwiżdż , Marta Tyran-Kamińska

In this paper, we present a kernel-based, multi-task Gaussian Process (GP) model for approximating the underlying function of an individual's mobility state using a time-inhomogeneous Markov Process with two states: moves and pauses. Our…

Machine Learning · Statistics 2023-06-22 Ekin Ugurel

External and internal factors may cause a system's parameter to vary with time before it stabilizes. This drift induces a regime shift when the parameter crosses a bifurcation. Here, we study the case of an infinite dimensional system: a…

Chaotic Dynamics · Physics 2020-10-14 Julia Cantisán , Jesús M. Seoane , Miguel A. F. Sanjuán

We introduce two non-homogeneous processes: a fractional non-homogeneous Poisson process of order $k$ and and a fractional non-homogeneous P\'olya-Aeppli process of order $k$. We characterize these processes by deriving their non-local…

Probability · Mathematics 2021-05-04 Tetyana Kadankova , Nikolai Leonenko , Enrico Scalas

The problem of characterizing all new-time transformations preserving the Poisson structure of a finitedimensional Poisson system is completely solved in a constructive way. As a corollary, this leads to a broad generalization of previously…

Mathematical Physics · Physics 2019-10-24 Benito Hernández-Bermejo

In audio signal processing, probabilistic time-frequency models have many benefits over their non-probabilistic counterparts. They adapt to the incoming signal, quantify uncertainty, and measure correlation between the signal's amplitude…

Signal Processing · Electrical Eng. & Systems 2019-02-13 William J. Wilkinson , Michael Riis Andersen , Joshua D. Reiss , Dan Stowell , Arno Solin

This paper proposes an online learning method of Gaussian process state-space model (GP-SSM). GP-SSM is a probabilistic representation learning scheme that represents unknown state transition and/or measurement models as Gaussian processes…

Robotics · Computer Science 2024-10-30 Soon-Seo Park , Young-Jin Park , Youngjae Min , Han-Lim Choi

We study the intermittent fluorescence of a single molecule, jumping from the "light on" to the "light off" state, as a Poisson process modulated by a fluctuating environment. We show that the quasi-periodic and quasi-deterministic…

Soft Condensed Matter · Physics 2009-11-11 Simone Bianco , Paolo Grigolini , Paolo Paradisi

We are studying stationary random processes with conditional polynomial moments that allow a continuous path modification. Processes with continuous path modification, are important because they are relatively easy to simulate. One does not…

Probability · Mathematics 2024-11-21 Paweł J. Szabłowski

We consider Markov processes, which describe e.g. queueing network processes, in a random environment which influences the network by determining random breakdown of nodes, and the necessity of repair thereafter. Starting from an explicit…

Probability · Mathematics 2015-03-03 H. Daduna , R. Szekli

Consider the distance between two i.i.d. and independent Poisson processes with arrival rate $\lambda>0$ and respective arrival times $X_1,X_2,\dots$ and $Y_1,Y_2,\dots$ on a line. We give a closed analytical formula for the %expected…

Discrete Mathematics · Computer Science 2017-08-21 Rafał Kapelko

This study in centered on models accounting for stochastic deformations of sample paths of random walks, embedded either in $\mathbb{Z}^2$ or in $\mathbb{Z}^3$. These models are immersed in multi-type particle systems with exclusion.…

Statistical Mechanics · Physics 2007-05-23 Guy Fayolle , Cyril Furtlehner
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