Based on papers from a conference held in Flint, Mich. Includes bibliographical references.

The Markovian Arrival Process: Some Future Directions / Marcel F. Neuts -- An Algorithm for the P(n, t) Matrices of a Continuous BMAP / Marcel F. Neuts and Jian-Min Li -- A Preemptive Priority Queue with Nonrenewal Inputs / Fumiaki Machihara -- Analysis of a Multiserver Delay-Loss System with a General Markovian Arrival Process / Valeri Naoumov, Udo R. Krieger and Dietmar Wagner -- Analysis of a Finite Capacity Multiserver Model with Nonpreemptive Priorities and Nonrenewal Input / Dietmar Wagner -- Matrix-Multiplicative Approach to Quasi-Birth-and-Death Processes Analysis / Valeri Naoumov -- A Level Crossing Analysis of the MAP/G/1 Queue / Qi-Ming He and E.M. Jewkes -- Performance Analysis and Optimal Threshold Policies for Queueing Systems with Several Heterogeneous Servers and Markov Modulated Arrivals / R.K. Boel and N.K. Talat -- Phase-Type Distributions and Related Point Processes: Fitting and Recent Advances / Soren Asmussen. Based on the proceedings of the first International Conference on Matrix-Analytic Methods (MAM) in Stochastic Models held recently in Flint, Michigan, this timely resource presents a general working knowledge of MAM through carefully designed tutorial articles and application papers. Written by leading international experts representing 11 countries, Matrix-Analytic Methods in Stochastic Models furnishes previously inaccessible information on MAM studies carried out in the former Soviet Union ... introduces the Markovian arrival process ... discusses the fitting of distributions to observed data ... shows how MAM can be used in level crossing analyses ... details the applications of MAM in numerous areas, including priority queues, Markov chains on a tree structure, and parameter approximation ... and much more. Containing key bibliographic citations and over 1000 display equations, Matrix-Analytic Methods in Stochastic Models is an excellent reference for applied mathematicians, probabilists, performance analysts, applied statisticians, biostatisticians, industrial engineers, operations researchers, and graduate-level students in these disciplines.