Markov chains provide a fundamental framework for modelling stochastic processes, where the next state depends solely on the current state. Hidden Markov models (HMMs) extend this framework by ...

Markov chain models and phase-type distributions have emerged as powerful tools in healthcare analytics, offering a robust framework for understanding and predicting patient trajectories throughout ...

Bunches of individual customers approach a single servicing facility according to a stationary compound Poisson process. The resulting waiting line process is studied in continuous time by the method ...

In this article we discuss the problem of assessing the performance of Markov chain Monte Carlo (MCMC) algorithms on the basis of simulation output. In essence, we extend the original ideas of Gelman ...

Until recently, Markov models and analytical methods were fairly obscure mathematical techniques rarely applied outside of academic settings. The advent of functional safety standards, particularly ...