Computing performability measures in Markov chains by means of matrix functions

Analysing reward measures of LARES performability models by discontinuous Markov chains

This paper presents a new method for specifying and analysing Markovian performability models. An extension of the LARES modelling language is considered which offers both delayed and immediate transitions, as well as rate and impulse rewards on whose basis different types of reward measures can be defined. The paper describes the evaluation path, starting from the modular and hierarchical LARE...

ETMCC: Model Checking Performability Properties of Markov Chains

Model Checking Markov Chains Markov chains are widely used for modelling the behaviour of computer and communication systems. A common goal of modelling is the estimation of performance and dependability measures of the system under study, such as throughput, buffer occupancy or mean time to failure. With model checking, the angle is somewhat different: Instead of conducting an analysis whose a...

Molecular Computing for Markov Chains

In this paper, it is presented a methodology for implementing arbitrarily constructed time-homogenous Markov chains with biochemical systems. Not only discrete but also continuous-time Markov chains are allowed to be computed. By employing chemical reaction networks (CRNs) as a programmable language, molecular concentrations serve to denote both input and output values. One reaction network is ...

Empirical Bayes Estimation in Nonstationary Markov chains

Estimation procedures for nonstationary Markov chains appear to be relatively sparse. This work introduces empirical  Bayes estimators  for the transition probability  matrix of a finite nonstationary  Markov chain. The data are assumed to be of  a panel study type in which each data set consists of a sequence of observations on N>=2 independent and identically dis...

Transient Markov Chains with Stationary Measures