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A continuous-time Markov process $X$ can be conditioned to be in a given state at a fixed time $T > 0$ using Doob's $h$-transform. This transform requires the typically intractable transition density of $X$. The effect of the $h$-transform…

Probability · Mathematics 2024-09-16 Marc Corstanje , Frank van der Meulen , Moritz Schauer

A general affine Markov semigroup is formulated as the convolution of a homogeneous one with a skew convolution semigroup. We provide some sufficient conditions for the regularities of the homogeneous affine semigroup and the skew…

Probability · Mathematics 2007-06-13 D. A. Dawson , Zenghu Li

We study the non-stationary Feller process with time varying coefficients. We obtain the exact probability distribution exemplified by its characteristic function and cumulants. In some particular cases we exactly invert the distribution…

Statistical Mechanics · Physics 2016-02-17 Jaume Masoliver

We prove a complete class theorem that characterizes \emph{all} stationary time reversible Markov processes whose finite dimensional marginal distributions (of all orders) are infinitely divisible. Aside from two degenerate cases (iid and…

Probability · Mathematics 2021-06-01 Robert L Wolpert , Lawrence D. Brown

In this work, we consider an inhomogeneous (discrete time) Markov chain and are interested in its long time behavior. We provide sufficient conditions to ensure that some of its asymptotic properties can be related to the ones of a…

Probability · Mathematics 2017-11-09 Michel Benaïm , Florian Bouguet , Bertrand Cloez

In this note, we give an original convergence result for products of independent random elements of motion group. Then we consider dynamic random walks which are inhomogeneous Markov chains whose transition probability of each step is, in…

Probability · Mathematics 2010-03-04 C. R. E. Raja , R. Schott

Historically time-reversibility of the transitions or processes underpinning Markov chain Monte Carlo methods (MCMC) has played a key r\^ole in their development, while the self-adjointness of associated operators together with the use of…

Probability · Mathematics 2019-06-17 Christophe Andrieu , Samuel Livingstone

For a general free L\'evy process, we prove the existence of its higher variation processes as limits in distribution, and identify the limits in terms of the L\'evy-It\^o representation of the original process. For a general free compound…

Operator Algebras · Mathematics 2023-04-07 Michael Anshelevich , Zhichao Wang

Semi-Markov processes are a generalization of Markov processes since the exponential distribution of time intervals is replaced with an arbitrary distribution. This paper provides an integro-differential form of the Kolmogorov's backward…

Probability · Mathematics 2017-09-20 Enzo Orsingher , Costantino Ricciuti , Bruno Toaldo

In this paper we introduce and analyze a class of diffusion type equations related to certain non-Markovian stochastic processes. We start from the forward drift equation which is made non-local in time by the introduction of a suitable…

Mathematical Physics · Physics 2009-11-13 Antonio Mura , Murad S. Taqqu , Francesco Mainardi

Semi-Markov processes generalize Markov processes by adding temporal memory effects as expressed by a semi-Markov kernel. We recall the path weight for a semi-Markov trajectory and the fact that thermodynamic consistency in equilibrium…

Statistical Mechanics · Physics 2022-04-15 Benjamin Ertel , Jann van der Meer , Udo Seifert

There are two natural notions of L\'evy processes in free probability: the first one has free increments with homogeneous distributions and the other has homogeneous transition probabilities. In the two cases one can associate a Nevanlinna…

Probability · Mathematics 2019-08-05 Philippe Biane

A variational formula for the asymptotic variance of general Markov processes is obtained. As application, we get a upper bound of the mean exit time of reversible Markov processes, and some comparison theorems between the reversible and…

Probability · Mathematics 2021-06-02 Lu-Jing Huang , Yong-Hua Mao , Tao Wang

A semi-Markov process is one that changes states in accordance with a Markov chain but takes a random amount of time between changes. We consider the generalisation to semi-Markov processes of the classical Lamperti law for the occupation…

Statistical Mechanics · Physics 2022-07-13 Théo Dessertaine , Claude Godrèche , Jean-Philippe Bouchaud

Markov processes play an important role in physics and the theory of open systems in particular. In this paper we study the asymptotic evolution of trace-nonincreasing homogenous quantum Markov processes (both types, discrete quantum Markov…

Quantum Physics · Physics 2019-02-19 Jaroslav Novotný , Jirí Maryška , Igor Jex

In a specific class of open quantum systems with finite and fixed numbers of collapsed quantum states, the semi-Markov process method is used to calculate the large deviations of the first passage time statistics. The core formula is an…

Statistical Mechanics · Physics 2024-10-10 Fei Liu , Shihao Xia , Shanhe Su

This paper is concerned with extensions of the classical Mar\v{c}enko-Pastur law to time series. Specifically, $p$-dimensional linear processes are considered which are built from innovation vectors with independent, identically distributed…

Statistics Theory · Mathematics 2015-04-03 Haoyang Liu , Alexander Aue , Debashis Paul

We construct a Markov process model to describe the evolution of labor division and its dynamical behavior is investigated by numerical simulations in detail. We have shown that under the mechanism of increasing returns, the division of…

Adaptation and Self-Organizing Systems · Physics 2007-05-23 Lei Chai , Dahui Wang , Jiawei Chen , Zengru Di

We give Hoeffding and Bernstein-type concentration inequalities for the largest eigenvalue of sums of random matrices arising from a Markov chain. We consider time-dependent matrix-valued functions on a general state space, generalizing…

Probability · Mathematics 2025-07-01 Joe Neeman , Bobby Shi , Rachel Ward

We study general properties for the family of stochastic processes with polynomial regression property, that is that every conditional moment of the process is a polynomial. It turns out that then there exists a family of polynomial…

Probability · Mathematics 2017-04-04 Paweł J. Szabłowski