A note on book covers: while we do our best to ensure the accuracy of cover images, ISBNs may at times be reused for different editions of the same title which may hence appear as a different cover.
This book contains material on compound Poisson random variables including an identity which can be used to efficiently compute moments, Poisson approximations, and coverage of the mean time spent in transient states as well as examples relating to the Gibb's sampler, the Metropolis algorithm and mean cover time in star graphs.
A note on book covers: while we do our best to ensure the accuracy of cover images, ISBNs may at times be reused for different editions of the same title which may hence appear as a different cover.
Complex stochastic processes explained with practical examples.
Who is this book for?
This book is perfect if you're interested in the mathematical underpinnings of stochastic processes. Its clear explanations and practical examples like the Gibb's sampler and Metropolis algorithm make complex ideas accessible. Whether you're studying or applying these concepts, you'll find it both insightful and useful.
