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A maximal inequality is an inequality which involves the (absolute) supremum $\sup_{s\leq t}|X_{s}|$ or the running maximum $\sup_{s\leq t}X_{s}$ of a stochastic process $(X_t)_{t\geq 0}$. We discuss maximal inequalities for several classes…

Probability · Mathematics 2023-03-28 Franziska Kühn , René L. Schilling

The multiplicative coalescent is a mean-field Markov process in which any pair of blocks coalesces at rate proportional to the product of their masses. In Aldous and Limic (1998) each extreme eternal version of the multiplicative coalescent…

Probability · Mathematics 2018-12-12 Vlada Limic

Under continuity and recurrence assumptions, we prove that the iteration of successive partial symmetrizations that form a time-homogeneous Markov process, converges to a symmetrization. We cover several settings, including the…

Probability · Mathematics 2018-08-21 Justin Dekeyser , Jean Van Schaftingen

We develop a general method for extending Markov processes to a larger state space such that the added points form a polar set. The so obtained extension is an improvement on the standard trivial extension in which case the process is made…

Probability · Mathematics 2019-09-06 Lucian Beznea , Iulian Cîmpean , Michael Röckner

We establish verifiable general sufficient conditions for exponential or subexponential ergodicity of Markov processes that may lack the strong Feller property. We apply the obtained results to show exponential ergodicity of a variety of…

Probability · Mathematics 2019-03-27 Oleg Butkovsky , Alexei Kulik , Michael Scheutzow

We give an intrinsic estimate of the number of connected components of the complementary set to the amoeba of an exponential sum with real spectrum improving the result of Forsberg, Passare and Tsikh in the polynomial case and that of…

Complex Variables · Mathematics 2019-04-11 James Silipo

The Law of the Iterated Logarithm for some Markov operators, which converge exponentially to the invariant measure, is established. The operators correspond to iterated function systems which, for example, may be used to generalize the cell…

Probability · Mathematics 2016-03-23 Sander C. Hille , Katarzyna Horbacz , Tomasz Szarek , Hanna Wojewódka

We develop a quasi-likelihood analysis procedure for a general class of multivariate marked point processes. As a by-product of the general method, we establish under stability and ergodicity conditions the local asymptotic normality of the…

Statistics Theory · Mathematics 2021-08-06 Simon Clinet

General birth-and-death as well as hopping stochastic dynamics of infinite particle systems in the continuum are considered. We derive corresponding evolution equations for correlation functions and generating functionals. General…

Mathematical Physics · Physics 2010-02-10 Dmitri L. Finkelshtein , Yuri G. Kondratiev , Maria Joao Oliveira

In this paper, we establish a version of the central limit theorem for Markov-Feller continuous time processes (with a Polish state space) that are exponentially ergodic in the bounded-Lipschitz distance and enjoy a continuous form of the…

Probability · Mathematics 2023-10-09 Dawid Czapla , Katarzyna Horbacz , Hanna Wojewódka-Ściążko

We consider the Markov chain approximations for singular stable-like processes. First we obtain properties of some Markov chains. Then we construct the approximating Markov chains and give a necessary condition for weak convergence of these…

Probability · Mathematics 2012-10-11 Fangjun Xu

Markov categories have recently turned out to be a powerful high-level framework for probability and statistics. They accommodate purely categorical definitions of notions like conditional probability and almost sure equality, as well as…

Probability · Mathematics 2026-02-12 Tobias Fritz , Tomáš Gonda , Antonio Lorenzin , Paolo Perrone , Dario Stein

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

We adapt ideas of Phong, Stein and Sturm and ideas of Ikromov and M\"uller from the continuous setting to various discrete settings, obtaining sharp bounds for exponential sums and the number of solutions to polynomial congruences for…

Number Theory · Mathematics 2012-02-14 James Wright

We study Markov processes associated with stochastic differential equations, whose non-linearities are gradients of convex functionals. We prove a general result of existence of such Markov processes and a priori estimates on the transition…

Probability · Mathematics 2007-05-23 Luigi Ambrosio , Giuseppe Savare , Lorenzo Zambotti

The Markov-Bernstein type inequalities between the norms of functions and of their derivatives are analysed for complex exponential polynomials. We establish a relation between the sharp constants in those inequalities and the stability…

Functional Analysis · Mathematics 2022-09-27 Vladimir Yu. Protasov

There are given sufficient conditions under which mixtures of dilations of L\'evy spectral measures, on a Hilbert space, are L\'evy measures again. We introduce some random integrals with respect to infinite dimensional L\'evy processes,…

Probability · Mathematics 2012-06-15 Zbigniew J. Jurek

Markov-modulated L\'evy processes with two different regimes of restarting are studied. These regimes correspond to the completely renewed process and to the process of Markov modulation, accompanied by jumps. We give explicit expressions…

Probability · Mathematics 2018-11-26 Nikita Ratanov

In this paper, we give an elementary proof of the additivity of the functional inverses of the resolvents of large $N$ random matrices, using recently developed matrix model techniques. This proof also gives a very natural generalization of…

Mathematical Physics · Physics 2009-10-31 P. Zinn-Justin

Exponential integrability properties of numerical approximations are a key tool for establishing positive rates of strong and numerically weak convergence for a large class of nonlinear stochastic differential equations. It turns out that…

Numerical Analysis · Mathematics 2020-08-10 Martin Hutzenthaler , Arnulf Jentzen , Xiaojie Wang