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Motivated by a model presented by S. Gudder, we study a quantum generalization of Markov chains and discuss the relation between these maps and open quantum random walks, a class of quantum channels described by S. Attal et al. We consider…

Quantum Physics · Physics 2016-08-10 Carlos F. Lardizabal , Rafael R. Souza

Let $(\xi_n)_{n=0}^\infty$ be a nonhomogeneous Markov chain taking values from finite state-space of $\mathbf{X}=\{1,2,\ldots,b\}$. In this paper, we will study the generalized entropy ergodic theorem with almost-everywhere and…

Probability · Mathematics 2015-01-19 Zhongzhi Wang , Weiguo Yang

The recently established spectral Favard theorem for bounded banded matrices admitting a positive bidiagonal factorization is applied to a broader class of Markov chains with bounded banded transition matrices, extending beyond the…

Probability · Mathematics 2026-01-27 Amílcar Branquinho , Ana Foulquié-Moreno , Manuel Mañas

We study time-changed Markov processes to speed up the convergence of Markov chain Monte Carlo (MCMC) algorithms. The time-changed process is defined by adjusting the speed of time of a base process via a user-chosen, state-dependent…

Computation · Statistics 2025-04-08 Andrea Bertazzi , Giorgos Vasdekis

In this study, a new extension of the Markov Renewal theory is introduced by allowing time to evolve in multiple dimensions. The resulting chains are referred to as multi-time Markov Renewal chains and since this extension is new, the state…

Probability · Mathematics 2025-08-21 Leonidas Kordalis , Samis Trevezas

We introduce the probabilistic sequential matrix factorization (PSMF) method for factorizing time-varying and non-stationary datasets consisting of high-dimensional time-series. In particular, we consider nonlinear Gaussian state-space…

Machine Learning · Statistics 2021-03-19 Ömer Deniz Akyildiz , Gerrit J. J. van den Burg , Theodoros Damoulas , Mark F. J. Steel

We present a new class of interacting Markov chain Monte Carlo algorithms for solving numerically discrete-time measure-valued equations. The associated stochastic processes belong to the class of self-interacting Markov chains. In contrast…

Probability · Mathematics 2010-09-30 Pierre Del Moral , Arnaud Doucet

This paper considers the normalized fundamental matrix for the northwest-corner (NW-corner) truncation of ergodic continuous-time Markov chains, technically, of their infinitesimal generators. We first present a limit formula for the…

Probability · Mathematics 2018-12-07 Hiroyuki Masuyama

In the present article, we analyse the behaviour of a new family of Kantorovich type sampling operators $(K_w^{\varphi}f)_{w>0}.$ First, we give a Voronovskaya type theorem for these Kantorovich generalized sampling series and a…

Classical Analysis and ODEs · Mathematics 2017-09-12 A. Sathish Kumar , P. Devaraj

We study long time behavior of a discrete time weakly interacting particle system, and the corresponding nonlinear Markov process in $\mathbb{R}^d$, described in terms of a general stochastic evolution equation. In a setting where the state…

Probability · Mathematics 2014-01-16 Amarjit Budhiraja , Abhishek Pal Majumder

We propose a novel Metropolis-Hastings algorithm to sample uniformly from the space of correlation matrices. Existing methods in the literature are based on elaborated representations of a correlation matrix, or on complex parametrizations…

Computation · Statistics 2019-10-18 Irene Córdoba , Gherardo Varando , Concha Bielza , Pedro Larrañaga

In this research the technology of complex Markov chains is applied to predict financial time series. The main distinction of complex or high-order Markov Chains and simple first-order ones is the existing of aftereffect or memory. The…

Statistical Finance · Quantitative Finance 2011-11-23 Vladimir Soloviev , Vladimir Saptsin , Dmitry Chabanenko

The solvability of the Riemann-Hilbert boundary value problem on the real line is described in the case when its matrix coefficient admits a Wiener-Hopf type factorization with bounded outer factors but rather general diagonal elements of…

Functional Analysis · Mathematics 2011-03-11 M. C. Camara , C. Diogo , Yu. I. Karlovich , I. M. Spitkovsky

We investigate multivariate regular variation in the context of time-homogeneous Markov chains on general vector spaces and in random coefficient linear models. In the first part, we show that the regular variation of the stationary…

Probability · Mathematics 2025-10-23 Piotr Dyszewski , Tamara Mika

In this study, we address the central issue of statistical inference for Markov jump processes using discrete time observations. The primary problem at hand is to accurately estimate the infinitesimal generator of a Markov jump process, a…

Methodology · Statistics 2024-12-19 F. Baltazar-Larios , Luz Judith R. Esparza

We show that the generation time -- a notion usually described in a biological context -- can be defined in a general way as a return time in a conveniently constructed finite Markov chain. The simple formula we obtain agrees with previous…

Populations and Evolution · Quantitative Biology 2018-03-20 François Bienvenu , Lloyd Demetrius , Stéphane Legendre

This paper deals with the time-varying high dimensional covariance matrix estimation. We propose two covariance matrix estimators corresponding with a time-varying approximate factor model and a time-varying approximate characteristic-based…

Econometrics · Economics 2019-10-29 Jaeheon Jung

We collect, scattered through literature, as well as we prove some new properties of two Markov processes that in many ways resemble Wiener and Ornstein--Uhlenbeck processes. Although processes considered in this paper were defined either…

Probability · Mathematics 2013-06-18 Paweł J. Szabłowski

We describe an exact approach for calculating transition probabilities and waiting times in finite-state discrete-time Markov processes. All the states and the rules for transitions between them must be known in advance. We can then…

Other Condensed Matter · Physics 2009-11-11 Semen A. Trygubenko , David J. Wales

Consider the global optimisation of a function $U$ defined on a finite set $V$ endowed with an irreducible and reversible Markov generator.By integration, we extend $U$ to the set $\mathcal{P}(V)$ of probability distributions on $V$ and we…

Functional Analysis · Mathematics 2024-04-16 Laurent Miclo , Nhat-Thang Le