The idea for this book came from the time the authors spent at the Statistics and Applied
Mathematical Sciences Institute (SAMSI) in Research Triangle Park in North Carolina …

Changes and additions are sprinkled throughout. Among the significant new features are:•
Markov-chain simulation (Sections 1. 3, 2. 6, 3. 6, 4. 3, 5. 4. 5, and 5. 5);• gradient estimation …

This tutorial presents an overview of model checking for both discrete and continuous-time
Markov chains (DTMCs and CTMCs). Model checking algorithms are given for verifying …

Although repetitive patterns of antigens are crucial for certain immune responses, an
understanding of how antibodies bind and dynamically interact with various spatial …

Continuous-time Markov chains (CTMCs) have been widely used to determine system
performance and dependability characteristics. Their analysis most often concerns the …

Containing a summary of several recent results on Markov-based input modeling in a
coherent notation, this book introduces and compares algorithms for parameter fitting and …

We consider the numerical evaluation of Markov model transient behavior. Our research is
motivated primarily by computer system dependability modeling. Other application areas …

In this paper, we show how to utilize the expectation-maximization (EM) algorithm for
efficient and numerical stable parameter estimation of the batch Markovian arrival process …

Markov and Markov reward models are widely used for the performance and reliability
analysis of computer and communication systems. Models of real systems often contain …

Numerical analysis based on uniformisation and statistical techniques based on sampling
and simulation are two distinct approaches for transient analysis of stochastic systems. We …