𝔖 Scriptorium
✦   LIBER   ✦

📁

Markov Chains: Gibbs Fields, Monte Carlo Simulation, and Queues

✍ Scribed by Pierre Bremaud


Publisher
Springer
Year
1999
Tongue
English
Leaves
455
Edition
Corrected
Category
Library

⬇  Acquire This Volume

No coin nor oath required. For personal study only.

✦ Synopsis


Primarily an introduction to the theory of stochastic processes at the undergraduate or beginning graduate level, the primary objective of this book is to initiate students in the art of stochastic modelling. However it is motivated by significant applications and progressively brings the student to the borders of contemporary research. Examples are from a wide range of domains, including operations research and electrical engineering. Researchers and students in these areas as well as in physics, biology and the social sciences will find this book of interest.

✦ Subjects


Математика;Теория вероятностей и математическая статистика;Теория случайных процессов;


📜 SIMILAR VOLUMES


Markov chains: Gibbs fields, Monte Carlo
✍ Pierre Bremaud 📂 Library 📅 1999 🏛 Springer 🌐 English

This book discusses both the theory and applications of Markov chains. The author studies both discrete-time and continuous-time chains and connected topics such as finite Gibbs fields, non-homogeneous Markov chains, discrete time regenerative processes, Monte Carlo simulation, simulated annealing,

Markov Chains - Gibbs Fields, Monte Carl
✍ Pierre Brémaud 📂 Library 📅 2020 🏛 Springer 🌐 English

This 2nd edition is a thoroughly revised and augmented version of the book with the same title published in 1999. The author begins with the elementary theory of Markov chains and very progressively brings the reader to more advanced topics. He gives a useful review of probability, making the book s

Markov Chains: Gibbs Fields, Monte Carlo
✍ Pierre Brémaud 📂 Library 📅 1999 🏛 Springer 🌐 English

Primarily an introduction to the theory of stochastic processes at the undergraduate or beginning graduate level, the primary objective of this book is to initiate students in the art of stochastic modelling. However it is motivated by significant applications and progressively brings the student to

Markov Chains: Gibbs Fields, Monte Carlo
✍ Pierre Bremaud 📂 Library 📅 2008 🏛 Springer 🌐 English

<span>In this book, the author begins with the elementary theory of Markov chains and very progressively brings the reader to the more advanced topics. He gives a useful review of probability that makes the book self-contained, and provides an appendix with detailed proofs of all the prerequisites f

Markov Chain Monte Carlo: Stochastic Sim
✍ Dani Gamerman, Hedibert Freitas Lopes 📂 Library 📅 2006 🏛 Chapman and Hall/CRC 🌐 English

While there have been few theoretical contributions on the Markov Chain Monte Carlo (MCMC) methods in the past decade, current understanding and application of MCMC to the solution of inference problems has increased by leaps and bounds. Incorporating changes in theory and highlighting new applicati