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This paper presents a method for calculating steady state probabilities of $M|E_r|c|K$ queueing systems. The infinitesimal generator matrix is used to define all possible states in the system and their transition probabilities. While this…

Systems and Control · Computer Science 2014-01-21 Stefan Hochrainer , Ronald Hochreiter , Georg Pflug

Markov chains are a convenient means of generating realizations of networks, since they require little more than a procedure for rewiring edges. If a rewiring procedure exists for generating new graphs with specified statistical properties,…

Social and Information Networks · Computer Science 2012-02-17 Jaideep Ray , Ali Pinar , C. Seshadhri

The main subject of the study in this paper is the simultaneous renewal time for two time-inhomogeneous Markov chains which start with arbitrary initial distributions. By a simultaneous renewal we mean the first time of joint hitting the…

Probability · Mathematics 2020-01-09 Vitaliy Golomoziy

We test a Markov chain approximation to the segment description (Li, 2007) of chaos (and turbulence) on a tent map, the Minea system, the H\'enon map, and the Lorenz system. For the tent map, we compute the probability transition matrix of…

Chaotic Dynamics · Physics 2010-02-05 Alexander Labovsky , Y. Charles Li

We consider trap models on Z^d, namely continuous time Markov jump process on Z^d with embedded chain given by a generic discrete time random walk, and whose mean waiting time at x is given by tau_x, with tau = (tau_x, x in Z^d) a family of…

Probability · Mathematics 2017-05-17 Luiz Renato Fontes , Pierre Mathieu

Invariance times are stopping times $\tau$ such that local martingales with respect to some reduced filtration and an equivalently changed probability measure, stopped before $\tau$ , are local martingales with respect to the original model…

Probability · Mathematics 2024-07-23 Stéphane Crépey

We compute the stationary distribution of a continuous-time Markov chain which is constructed by gluing together two finite, irreducible Markov chains by identifying a pair of states of one chain with a pair of states of the other and…

Probability · Mathematics 2015-10-22 Bence Mélykúti , Peter Pfaffelhuber

Given an ergodic finite-state Markov chain, let M_{iw} denote the mean time from i to equilibrium, meaning the expected time, starting from i, to arrive at a state selected randomly according to the equilibrium measure w of the chain. John…

Probability · Mathematics 2009-09-16 Peter G. Doyle

We develop some sufficient conditions for the stochastic ordering between hitting times, in a fixed state, for two Markov chains. In particular, we focus attention on the so called \emph{skip-free} case. In the analysis of such a case, we…

Probability · Mathematics 2014-03-25 Emilio De Santis , Fabio Spizzichino

An aperiodic and irreducible Markov chain on a finite state space converges to its stationary distribution. When convergence to equilibrium is measured by total variation distance, there exists an optimal coupling and a maximal coupling…

Probability · Mathematics 2015-04-01 Agnes Coquio

To find the number of assignments of zeros and ones satisfying a specific Knapsack Problem is $\#P$ hard, so only approximations are envisageable. A Markov chain allowing uniform sampling of all possible solutions is given by Luby, Randall…

Combinatorics · Mathematics 2018-03-20 Koko K. Kayibi , S. Pirzada , Carrie Rutherford

In this paper, we provide a solution to two problems which have been open in default time modeling in credit risk. We first show that if $\tau$ is an arbitrary random (default) time such that its Az\'ema's supermartingale…

Risk Management · Quantitative Finance 2008-12-02 Delia Coculescu , Ashkan Nikeghbali

We consider continuous-time Markov chains on integers which allow transitions to adjacent states only, with alternating rates. We give explicit formulas for probability generating functions, and also for means, variances and state…

Probability · Mathematics 2019-10-30 Luisa Beghin , Claudio Macci , Barbara Martinucci

Let $T\$ be a stopping time associated with a sequence of independent random variables $Z_{1},Z_{2},...$ . By applying a suitable change in the probability measure we present relations between the moment or probability generating functions…

Statistics Theory · Mathematics 2011-06-28 M. V. Boutsikas , A. C. Rakitzis , D. L. Antzoulakos

We consider random walks in which the walk originates in one set of nodes and then continues until it reaches one or more nodes in a target set. The time required for the walk to reach the target set is of interest in understanding the…

Systems and Control · Computer Science 2019-01-11 Andrew Clark , Basel Alomair , Linda Bushnell , Radha Poovendran

This paper is concerned with the development of rigorous approximations to various expectations associated with Markov chains and processes having non-stationary transition probabilities. Such non-stationary models arise naturally in…

Probability · Mathematics 2018-05-07 Zeyu Zheng , Harsha Honnappa , Peter W. Glynn

Motivated by robotic surveillance applications, this paper studies the novel problem of maximizing the return time entropy of a Markov chain, subject to a graph topology with travel times and stationary distribution. The return time entropy…

Optimization and Control · Mathematics 2018-05-29 Xiaoming Duan , Mishel George , Francesco Bullo

Consider a system of coalescing random walks where each individual performs random walk over a finite graph G, or (more generally) evolves according to some reversible Markov chain generator Q. Let C be the first time at which all walkers…

Probability · Mathematics 2010-12-17 Roberto Imbuzeiro Oliveira

Markov chains are convenient means of generating realizations of networks with a given (joint or otherwise) degree distribution, since they simply require a procedure for rewiring edges. The major challenge is to find the right number of…

Social and Information Networks · Computer Science 2012-11-01 J. Ray , A. Pinar , C. Seshadhri

This paper formulates the completion time $\tau$ of a project network as $ \tau =\|\mathbf{R} \mathbf{t} \|_\infty $ where the rows of $\mathbf{R}$ are simple paths of the network and $\mathbf{t}$ is a column vector representing the…