Grassmann W.K. Computational Probability

N.-Y.: Springer, 2000. - 490p.Great advances have been made in recent years in the field of computational probability. In particular, the state of the art - as it relates to queuing systems, stochastic Petri-nets and systems dealing with reliability - has benefited significantly from these advances. The objective of this book is to make these topics accessible to researchers, graduate students, and practitioners. Great care was taken to make the exposition as clear as possible. Every line in the book has been evaluated, and changes have been made whenever it was felt that the initial exposition was not clear enough for the intended readership.Computational Probability: Challenges and Limitations
Tools for Formulating Markov Models
Transient Solutions for Markov Chains
Numerical Methods for Computing Stationary Distributions of Finite Irreducible Markov Chains
Stochastic Automata Networks
Matrix Analytic Methods
Use of Characteristic Roots for Solving Infinite State Markov Chains
An Introduction to Numerical Transform Inversion and Its Application to Probability Models
Optimal Control of Markov Chains
On Numerical Computations of Some Discrete-Time Queues
The Product form Tool for Queueing Networks
Techniques for System Dependability Evaluation