… the parameters of the Markov model to match observed signal … and implementation of
Markov modelling techniques have … introduction to the theory of Markov models, and to illustrate …

… Both cellular automata (CA) and the Markov model have great advantages in the study on …
The Markov model for land use changes has been widely used, but with the traditional Markov …

… Statistical models called hidden Markov models are a recurring theme in computational
biology. What are hidden Markov models, and why are they so useful for so many different …

… In a healthcare context, Markov models are particularly suited to modelling … use of Markov
models for economic evaluation of healthcare interventions. The intuitive way in which Markov …

… The precise definition of the term "Markov chain" as used … Markov process is a special type
of stochastic process distinguished by a certain Markov property; a Markov chain is a Markov …

… We have a Markov family of random functions if to each x E E there corresponds a Markov
random function Xre = (xf, ere, Jlf, pre) in the state space (E, fJU), and moreover: 3.2.B. P (t, x, F…

An overview of statistical and information-theoretic aspects of hidden Markov processes (HMPs)
is presented. An HMP is a discrete-time finite-state homogeneous Markov chain …

This is the revised and augmented edition of a now classic book which is an introduction to
sub-Markovian kernels on general measurable spaces and their associated homogeneous …

The aim of this book is to outline the recent development of Markov chain models and their
applications in queueing systems, manufacturing systems, remanufacturing systems, …

… types of homogeneous finite Markov chains: absorbing and … role of homogeneous
infinite Markov chains in mathematical … finite Markov chain theory; and a study of Markovian …