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Related papers: Time-changed Poisson processes of order $k$

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We provide a detailed proof of Proposition 3.1 in the paper titled ``Backstepping control of a class of space-time-varying linear parabolic PDEs via time invariant kernel functions''. In the paper titled ``Backstepping control of a class of…

Analysis of PDEs · Mathematics 2023-01-27 Qiaoling Chen , Jun Zheng , Guchuan Zhu

For $S$ a subordinator and $\Pi_n$ an independent Poisson process of intensity $ne^{-x}, x>0,$ we are interested in the number $K_n$ of gaps in the range of $S$ that are hit by at least one point of $\Pi_n$. Extending previous studies in…

Probability · Mathematics 2007-05-23 Andrew D. Barbour , Alexander V. Gnedin

In this paper, we define a tempered space-time fractional negative binomial process (TSTFNBP) by subordinating the fractional Poisson process with an independent tempered Mittag-Leffler L\'{e}vy subordinator. We study its distributional…

Probability · Mathematics 2024-09-12 Shilpa , Ashok Kumar Pathak , Aditya Maheshwari

We study two time-changed variants of the birth-death process with catastrophe where the time-changing components are the first hitting times of the stable subordinator and the tempered stable subordinator. For both the processes, we derive…

Probability · Mathematics 2026-02-10 Kuldeep Kumar Kataria , Rohini Bhagwanrao Pote

The paper contains a basic course on classical Risk Theory for a compound Poisson process. It is based on probabilistic proofs using the method of the "Ballot Theorem" introduced by Tackas. This provides elegant and direct proofs. Also…

Probability · Mathematics 2011-10-13 Anders Martin-Löf , Anders Sköllermo

Multivariate Poisson processes have many important applications in Insurance, Finance, and many other areas of Applied Probability. In this paper we study the backward simulation approach to modelling multivariate Poisson processes and…

Methodology · Statistics 2017-10-30 Michael Chiu , Kenneth R. Jackson , Alexander Kreinin

We introduce a non-homogeneous version of the generalized counting process (GCP), namely, the non-homogeneous generalized counting process (NGCP). We time-change the NGCP by an independent inverse stable subordinator to obtain its…

Probability · Mathematics 2022-10-11 K. K. Kataria , M. Khandakar , P. Vellaisamy

In this second part, we analyze the dissipation properties of Generalized Poisson-Kac (GPK) processes, considering the decay of suitable $L^2$-norms and the definition of entropy functions. In both cases, consistent energy dissipation and…

Statistical Mechanics · Physics 2017-08-02 Massimiliano Giona , Antonio Brasiello , Silvestro Crescitelli

We analyze some basic issues associated with Generalized Poisson-Kac (GPK) stochastic processes, starting from the extended notion of the Markovian condition. The extended Markovian nature of GPK processes is established, and the…

Statistical Mechanics · Physics 2017-03-08 Massimiliano Giona , Antonio Brasiello , Silvestro Crescitelli

Consider a sequence $\{(X_{i}, Y_{i})\}$ of independent and identically distributed random vectors, with joint distribution bivariate Sarmanov. This is a natural set-up for discrete time financial risk models with insurance risks. Of…

Probability · Mathematics 2016-04-19 Krishanu Maulik , Moumanti Podder

We study Markov processes conditioned so that their local time must grow slower than a prescribed function. Building upon recent work on Brownian motion with constrained local time in [5] and [33], we study transience and recurrence for a…

Probability · Mathematics 2020-12-24 Adam Barker

Fractional Poisson processes, a rapidly growing area of non-Markovian stochastic processes, are useful in statistics to describe data from counting processes when waiting times are not exponentially distributed. We show that the fractional…

Classical Analysis and ODEs · Mathematics 2013-10-14 Markus Kreer , Ayse Kizilersu , Anthony W. Thomas

In this paper, we introduce a risk process, namely, the mixed fractional risk process (MFRP) in which the number of claims in the associated claim process are modelled using the mixed fractional Poisson process (MFPP). The covariance…

Probability · Mathematics 2021-06-23 K. K. Kataria , M. Khandakar

A non-Markovian counting process, the `generalized fractional Poisson process' (GFPP) introduced by Cahoy and Polito in 2013 is analyzed. The GFPP contains two index parameters $0<\beta\leq 1$, $\alpha >0$ and a time scale parameter.…

Statistical Mechanics · Physics 2020-04-22 Thomas M. Michelitsch , Alejandro P. Riascos

In this paper, we introduce drifted versions of the generalized counting process (GCP) with a deterministic drift and a random drift. The composition of stable subordinator with an independent inverse stable subordinator is taken as the…

Probability · Mathematics 2025-02-04 Mostafizar Khandakar , Manisha Dhillon , Kuldeep Kumar Kataria

Let $G_{k,n}$ be a group of permutations of $kn$ objects which permutes things independently in disjoint blocks of size $k$ and then permutes the blocks. We investigate the probabilistic and/or enumerative aspects of random elements of…

Probability · Mathematics 2025-04-29 Persi Diaconis , Nathan Tung

In this paper we will take under consideration subordinators and their inverse processes (hitting-times). We will present in general the governing equations of such processes by means of convolution-type integro-differential operators…

Probability · Mathematics 2014-07-24 Bruno Toaldo

In this paper we give few expressions and asymptotics of ruin probabilities for a Markov modulated risk process for various regimes of a time horizon, initial reserves and a claim size distribution. We also consider few versions of the ruin…

Probability · Mathematics 2021-10-05 Zbigniew Palmowski

We use the two-time scale subordination in order to describe dynamical processes in continuous media with a long-term memory. Our consideration touches two physical examples in detail. First we study a temporal evolution of the species…

Statistical Mechanics · Physics 2011-11-15 Aleksander Stanislavsky , Karina Weron

A general theory is developed to study individual based models which are discrete in time. We begin by constructing a Markov chain model that converges to a one-dimensional map in the infinite population limit. Stochastic fluctuations are…

Statistical Mechanics · Physics 2014-06-03 Joseph D. Challenger , Duccio Fanelli , Alan J. McKane
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