Phase type distributions are widely applicable modeling and statistical tools for non-negative random quantities. They are built on Markov chains, which provide a simple, intuitive stochastic interpretation for their use. Phase Type Distribution starts from the Markov chain-based definition of phase type distributions and presents many interesting properties, which follow from the basic definition.

As a general family of non-negative distributions with nice analytical properties, phase type distributions can be used for approximating experimental distributions by fitting or by moments matching; and, for discrete event simulation of real word systems with stochastic timing, such as production systems, service operations, communication networks, etc. This book summarizes the up-to-date fitting, matching and simulation methods, and presents the limits of flexibility of phase type distributions of a given order.

Additionally, this book lists numerical examples that support the intuitive understanding of the analytical descriptions and software tools that handle phase type distributions.