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We classify all functions which, when applied term by term, leave invariant the sequences of moments of positive measures on the real line. Rather unexpectedly, these functions are built of absolutely monotonic components, or reflections of…

Classical Analysis and ODEs · Mathematics 2022-05-17 Alexander Belton , Dominique Guillot , Apoorva Khare , Mihai Putinar

This is a survey of results about permanental processes, real valued positive processes which are a generalization of squares of Gaussian processes. In a certain sense the symmetric positive definite function that determines a Gaussian…

Probability · Mathematics 2010-08-23 Hana Kogan , Michael B. Marcus , Jay Rosen

Suppose that P_{\theta}(g) is a linear functional of a Dirichlet process with shape \theta H, where \theta >0 is the total mass and H is a fixed probability measure. This paper describes how one can use the well-known Bayesian prior to…

Statistics Theory · Mathematics 2007-06-13 Lancelot F. James

We consider a general piecewise deterministic Markov process (PDMP) $X=\{X_t\}_{t\geqslant 0}$ with measure-valued generator $\mathcal{A}$, for which the conditional distribution function of the inter-occurrence time is not necessarily…

Probability · Mathematics 2017-04-27 Zhaoyang Liu , Yuying Liu , Guoxin Liu

Dirichlet averages of multivariate functions are employed for a derivation of basic recurrence formulas for the moments of multivariate Dirichlet splines. An algorithm for computing the moments of multivariate simplex splines is presented.…

Classical Analysis and ODEs · Mathematics 2025-10-20 Edward Neuman , Patrick J. Van Fleet

We are studying stationary random processes with conditional polynomial moments that allow a continuous path modification. Processes with continuous path modification, are important because they are relatively easy to simulate. One does not…

Probability · Mathematics 2024-11-21 Paweł J. Szabłowski

We offer a new proof of the classical law of large numbers for a general class of branching Markov processes based on the asymptotic behaviour of the moments developed in \cite{bmoments, gonzalez2022erratum}. Moreover, we show that the law…

Probability · Mathematics 2025-12-01 Christopher B. C. Dean , János Engländer , Emma Horton

Piecewise-deterministic Markov processes form a general class of non-diffusion stochastic models that involve both deterministic trajectories and random jumps at random times. In this paper, we state a new characterization of the jump rate…

Methodology · Statistics 2017-05-03 Romain Azaïs , Alexandre Genadot

We give some relationships between the first Dirichlet eigenvalues and the exit time moments for the general symmetric Markov processes. As applications, we present some examples, including symmetric diffusions and $\alpha$-stable…

Probability · Mathematics 2022-06-22 Lu-Jing Huang , Tao Wang

For a general class of diffusion processes with multiplicative noise, describing a variety of physical as well as financial phenomena, mostly typical of complex systems, we obtain the analytical solution for the moments at all times. We…

Statistical Mechanics · Physics 2010-03-18 Giacomo Bormetti , Danilo Delpini

For a finite state Markov process and a finite collection $\{ \Gamma_k, k \in K \}$ of subsets of its state space, let $\tau_k$ be the first time the process visits the set $\Gamma_k$. We derive explicit/recursive formulas for the joint…

Probability · Mathematics 2014-03-03 Tomasz R. Bielecki , Monique Jeanblanc , Ali Devin Sezer

Computation of moments of transformed random variables is a problem appearing in many engineering applications. The current methods for moment transformation are mostly based on the classical quadrature rules which cannot account for the…

Methodology · Statistics 2017-01-06 Jakub Prüher , Ondřej Straka

Concentration properties of functionals of general Poisson processes are studied. Using a modified $\Phi$-Sobolev inequality a recursion scheme for moments is established, which is of independent interest. This is applied to derive moment…

Probability · Mathematics 2022-03-17 Anna Gusakova , Holger Sambale , Christoph Thaele

Methods were initiated by Mark Kac and Richard Feynman to evaluate random functionals of the form $\int^t_0V(X_s)ds$ for a nonnegative $V$ and a Markov process $X_t$. Their results evolved into the well known Feynman Kac formula.…

Probability · Mathematics 2025-01-22 Charles Hagwood

This article studies Markovian stochastic motion of a particle on a graph with finite number of nodes and periodically time-dependent transition rates that satisfy the detailed balance condition at any time. We show that under general…

Mesoscale and Nanoscale Physics · Physics 2015-06-03 Vladimir Y. Chernyak , John R. Klein , Nikolai A. Sinitsyn

In this paper, we establish moment and Bernstein-type inequalities for additive functionals of geometrically ergodic Markov chains. These inequalities extend the corresponding inequalities for independent random variables. Our conditions…

Probability · Mathematics 2023-06-16 Alain Durmus , Eric Moulines , Alexey Naumov , Sergey Samsonov

We revisit affine diffusion processes on general and on the canonical state space in particular. A detailed study of theoretic and applied aspects of this class of Markov processes is given. In particular, we derive admissibility conditions…

Probability · Mathematics 2009-10-10 Damir Filipovic , Eberhard Mayerhofer

For the multivariate COGARCH process, we obtain explicit expressions for the second-order structure of the "squared returns" process observed on an equidistant grid. Based on this, we present a generalized method of moments estimator for…

Statistics Theory · Mathematics 2021-02-03 Thiago do Rêgo Sousa , Robert Stelzer

The authors present a method of indicator random processes, applicable to constructing models of jump processes associated with diffusion process. Indicator random processes are processes that take only two values: 1 and 0, in accordance…

Dynamical Systems · Mathematics 2024-02-06 Valery Doobko , Elena Karachanskaya

This note develops shortly the theory of time-inhomogeneous additive functionals and is a useful support for the analysis of time-dependent Markov processes and related topics. It is a significant tool for the analysis of BSDEs in law. In…

Probability · Mathematics 2017-08-21 Adrien Barrasso , Francesco Russo
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