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We consider consistent diffusion dynamics, leaving the celebrated Hua-Pickrell measures, depending on a complex parameter $s$, invariant. These, give rise to Feller-Markov processes on the infinite dimensional boundary $\Omega$ of the…

Probability · Mathematics 2019-02-15 Theodoros Assiotis

We consider diffusion processes in Hilbert spaces with constant non-degenerate diffusion operators and show that, under broad assumptions on the drift, the transition probabilities of the process are positive on ellipsoids associated with…

Probability · Mathematics 2016-02-09 Oxana Manita

For general penalized Markov processes with soft killing, we propose a simple criterion ensuring uniform convergence of conditional distributions in Wasserstein distance to a unique quasi-stationary distribution. We give several examples of…

Probability · Mathematics 2025-11-13 Nicolas Champagnat , Edouard Strickler , Denis Villemonais

Chernoff approximations of Feller semigroups and the associated diffusion processes in Riemannian manifolds are studied. The manifolds are assumed to be of bounded geometry, thus including all compact manifolds and also a wide range of…

Functional Analysis · Mathematics 2022-10-17 Sonia Mazzucchi , Valter Moretti , Ivan Remizov , Oleg Smolyanov

A general approach to transference principles for discrete and continuous operator (semi)groups is described. This allows to recover the classical transference results of Calder\'on, Coifman and Weiss and of Berkson, Gillespie and Muhly and…

Functional Analysis · Mathematics 2010-10-26 Markus Haase

The recently introduced two-parameter Poisson-Dirichlet diffusion extends the infinitely-many-neutral-alleles model, related to Kingman's distribution and to Fleming-Viot processes. The role of the additional parameter has been shown to…

Probability · Mathematics 2016-01-26 Pierpaolo De Blasi , Matteo Ruggiero , Dario Spano'

The aim of this paper is to study some continuous-time bivariate Markov processes arising from group representation theory. The first component (level) can be either discrete (quasi-birth-and-death processes) or continuous (switching…

Probability · Mathematics 2016-10-06 Manuel D. de la Iglesia , Pablo Román

In this article we present the Durrmeyer variant of generalized Bernstein operators that preserve the constant functions involving non-negative parameter ?. We derive the approximation behaviour of these operators including global…

Classical Analysis and ODEs · Mathematics 2018-08-07 Arun Kajla , Meenu Goyal

This paper continues the research project launched in [Constr. Approx. (2025) https://doi.org/10.1007/s00365-023-09675-9] and aimed at studying time-inhomogeneous one-dimensional branching processes (mainly on a continuous but also on a…

Probability · Mathematics 2025-12-16 Pavel Gumenyuk , Takahiro Hasebe , José-Luis Pérez

The paper deals with a certain class of random evolutions. We develop a construction that yields an invariant measure for a continuous-time Markov process with random transitions. The approach is based on a particular way of constructing…

Probability · Mathematics 2015-10-20 Y. Belopolskaya , Y. Suhov

$\Lambda$-Wright--Fisher processes provide a robust framework to describe the type-frequency evolution of an infinite neutral population. We add a polynomial drift to the corresponding stochastic differential equation to incorporate…

Probability · Mathematics 2023-04-26 Fernando Cordero , Sebastian Hummel , Emmanuel Schertzer

The article is devoted to the application of multiple Fourier-Legendre series to implementation of strong exponential Milstein and Wagner-Platen methods for non-commutative semilinear stochastic partial differential equations with…

Probability · Mathematics 2022-03-15 Dmitriy F. Kuznetsov

When is it possible to interpret a given Markov process as a L\'evy-like process? Since the class of L\'evy processes can be defined by the relation between transition probabilities and convolutions, the answer to this question lies in the…

Probability · Mathematics 2020-09-08 Rúben Sousa , Manuel Guerra , Semyon Yakubovich

A new family of probability distributions $\beta_{M, N},$ $M=0\cdots N,$ $N\in\mathbb{N}$ on the unit interval $(0, 1]$ is defined by the Mellin transform. The Mellin transform of $\beta_{M, N}$ is characterized in terms of products of…

Probability · Mathematics 2014-02-26 Dmitry Ostrovsky

The purpose of this paper is to study the dynamical behavior of the sequence produced by a forward-backward algorithm involving two random maximal monotone operators and a sequence of decreasing step sizes. Defining a mean monotone operator…

Optimization and Control · Mathematics 2016-07-05 Pascal Bianchi , Walid Hachem

The Pearson family of ergodic diffusions with a quadratic diffusion coefficient and a linear force are characterized by explicit dynamics of their integer moments and by explicit relaxation spectral properties towards their steady state.…

Statistical Mechanics · Physics 2023-08-14 Cecile Monthus

Bernstein processes are Brownian diffusions that appear in Euclidean Quantum Mechanics. Knowledge of the symmetries of the Hamilton-Jacobi-Bellman equation associated with these processes allows one to obtain relations between stochastic…

Probability · Mathematics 2011-10-28 Paul Lescot

We consider an extended birth-death-immigration process defined on a lattice formed by the integers of $d$ semiaxes joined at the origin. When the process reaches the origin, then it may jumps toward any semiaxis with the same rate. The…

Probability · Mathematics 2016-06-07 Antonio Di Crescenzo , Barbara Martinucci , Abdelaziz Rhandi

We adopt an operator-theoretic perspective to study convergence of linear fixed-point iterations and discrete- time linear systems. We mainly focus on the so-called Krasnoselskij-Mann iteration x(k+1) = ( 1 - \alpha(k) ) x(k) + \alpha(k) A…

Optimization and Control · Mathematics 2018-03-29 Giuseppe Belgioioso , Filippo Fabiani , Franco Blanchini , Sergio Grammatico

We propose a general formalism of iterated random functions with semigroup property, under which exact and approximate Bayesian posterior updates can be viewed as specific instances. A convergence theory for iterated random functions is…

Machine Learning · Statistics 2013-11-05 Arash A. Amini , XuanLong Nguyen