MCMC from Scratch: A Practical Introduction to Markov Chain Monte Carlo

This textbook provides an introduction to Markov Chain Monte Carlo (MCMC) for beginners, covering the basics of the technique and its applications in various fields. It includes examples, exercises, and sample codes to help readers understand and apply MCMC.

Format: Hardback
Length: 194 pages
Publication date: 28 July 2022
Publisher: Springer Verlag, Singapore

This comprehensive textbook provides a thorough introduction to Markov Chain Monte Carlo (MCMC) without requiring advanced mathematical or programming expertise. MCMC is a powerful technique that finds wide application in diverse fields such as Bayesian statistics, quantum physics, machine learning, computer science, computational biology, and mathematical economics. The book's main objective is to equip readers with a solid understanding of MCMC and empower them to write their simulation codes independently.

The content is organized into six chapters. Chapter 2 introduces the Monte Carlo algorithm and highlights its advantages, while Chapter 3 provides a general overview of MCMC. Chapter 4 illustrates the core principles of MCMC using a simple example of the Metropolis algorithm. Chapter 5 explores the HMC, Gibbs sampling, and Metropolis-Hastings algorithms, discussing their strengths, limitations, and potential pitfalls. Chapter 6 showcases various applications of MCMC, including a wealth of examples and exercises with solutions, sample codes, and additional mathematical topics in the Appendix.

Designed for students and beginners in various fields, this textbook offers a valuable resource for those seeking to delve into the world of MCMC and its practical applications.

Weight: 514g
Dimension: 235 x 155 (mm)
ISBN-13: 9789811927140
Edition number: 1st ed. 2022