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We prove It{\^o}'s formula for the flow of measures associated with a jump process defined by a drift, an integral with respect to a Poisson random measure and with respect to the associated compensated Poisson random measure. We work in…

Probability · Mathematics 2022-11-30 Thomas Cavallazzi

This paper first strictly proved that the growth of the second moment of a large class of Gaussian processes is not greater than power function and the covariance matrix is strictly positive definite. Under these two conditions, the maximum…

Statistics Theory · Mathematics 2022-07-21 Shifei Luo

In the context of order statistics of discrete time random walks (RW), we investigate the statistics of the gap, $G_n$, and the number of time steps, $L_n$, between the two highest positions of a Markovian one-dimensional random walker,…

Statistical Mechanics · Physics 2014-09-17 Satya N. Majumdar , Philippe Mounaix , Gregory Schehr

The filtering equations associated to a partially observed jump diffusion model $(Z_t)_{t\in [0,T]}=(X_t,Y_t)_{t\in [0,T]}$, driven by Wiener processes and Poisson martingale measures are considered. Building on results from two preceding…

Probability · Mathematics 2022-11-15 Fabian Germ , István Gyöngy

We study the order statistics of a random walk (RW) of $n$ steps whose jumps are distributed according to symmetric Erlang densities $f_p(\eta)\sim |\eta|^p \,e^{-|\eta|}$, parametrized by a non-negative integer $p$. Our main focus is on…

Statistical Mechanics · Physics 2020-03-03 Matteo Battilana , Satya N. Majumdar , Gregory Schehr

We study a one-dimensional Markov modulated random walk with jumps. It is assumed that amplitudes of jumps as well as a chosen velocity regime are random and depend on a time spent by the process at a previous state of the underlying Markov…

Probability · Mathematics 2013-03-13 Nikita Ratanov

We study the statistical properties of jump processes in a bounded domain that are driven by Poisson white noise. We derive the corresponding Kolmogorov-Feller equation and provide a general representation for its stationary solutions.…

Statistical Mechanics · Physics 2018-10-16 S. I. Denisov , Yu. S. Bystrik

We consider one-dimensional discrete-time random walks (RWs) of $n$ steps, starting from $x_0=0$, with arbitrary symmetric and continuous jump distributions $f(\eta)$, including the important case of L\'evy flights. We study the statistics…

Statistical Mechanics · Physics 2023-11-22 Benjamin De Bruyne , Satya N. Majumdar , Gregory Schehr

We consider a L\'evy process reflected at the origin with additional i.i.d. collapses that occur at Poisson epochs, where a collapse is a jump downward to a state which is a random fraction of the state just before the jump. We first study…

Probability · Mathematics 2025-01-17 Onno Boxma , Offer Kella , David Perry

This paper deals with Poisson processes on an arbitrary measurable space. Using a direct approach, we derive formulae for moments and cumulants of a vector of multiple Wiener-It\^o integrals with respect to the compensated Poisson process.…

Probability · Mathematics 2014-07-08 Guenter Last , Mathew D. Penrose , Matthias Schulte , Christoph Thaele

We investigate extreme value statistics (EVS) of general discrete time and continuous space symmetric jump processes. We first show that for unbounded jump processes, the semi-infinite propagator $G_0(x,n)$, defined as the probability for a…

Statistical Mechanics · Physics 2023-09-08 Jérémie Klinger , Raphaël Voituriez , Olivier Bénichou

We study the random acceleration model, which is perhaps one of the simplest, yet nontrivial, non-Markov stochastic processes, and is key to many applications. For this non-Markov process, we present exact analytical results for the…

Statistical Mechanics · Physics 2019-09-04 Satya N. Majumdar , Alberto Rosso , Andrea Zoia

A continuous time mixed state branching process is constructed as the scaling limits of two-type Galton-Watson processes. The process can also be obtained by the pathwise unique solution to a stochastic equation system. From the stochastic…

Probability · Mathematics 2021-04-28 Shukai Chen , Zenghu Li

The boundary crossing probability of a Poisson process with $n$ jumps is a fundamental quantity with numerous applications. We present a fast $O(n^2 \log n)$ algorithm to calculate this probability for arbitrary upper and lower boundaries.

Computation · Statistics 2019-09-16 Amit Moscovich , Boaz Nadler

We consider a particle moving in continuous time as a Markov jump process; its discrete chain is given by an ordinary random walk on ${\mathbb Z}^d$ , and its jump rate at $({\mathbf x},t)$ is given by a fixed function $\varphi$ of the…

Probability · Mathematics 2025-01-03 Luiz Renato Fontes , Pablo Almeida Gomes , Maicon Aparecido Pinheiro

We consider parameter estimation of stochastic differential equations driven by a Wiener process and a compound Poisson process as small noises. The goal is to give a threshold-type quasi-likelihood estimator and show its consistency and…

Statistics Theory · Mathematics 2023-12-20 Mitsuki Kobayashi , Yasutaka Shimizu

In this paper, we study the Galton-Watson process in the random environment for the particular case when the number of the offsprings in each generation has the fractional linear generation function with random parameters. In this case, the…

Probability · Mathematics 2020-12-01 Dan Han , Stanislav Molchanov , Yanjmaa Jutmaan

We study the distribution of the 'gap time', the first time that a large gap appears, in the spatial birth and death point process on $[0,1]$ in which particles are added uniformly in space at rate $\lambda$ and are removed independently at…

Probability · Mathematics 2025-12-05 Eric Foxall , Clément Soubrier

Representations of branching Markov processes and their measure-valued limits in terms of countable systems of particles are constructed for models with spatially varying birth and death rates. Each particle has a location and a "level,"…

Probability · Mathematics 2011-04-11 Thomas G. Kurtz , Eliane R. Rodrigues

A possibly time-dependent transition intensity matrix or generator $(Q(t))$ characterizes the law of a Markov jump process (MP). For a time homogeneous MP, the transition probability matrix (TPM) can be expressed as a matrix exponential of…

Methodology · Statistics 2025-07-23 Dario Gasbarra , Sangita Kulathinal , Etienne Sebag