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MCMC from Scratch A Practical Introduction to Markov Chain Monte Carlo

Hanada, Masanori Matsuura, So
Heftet / 2023 / Engelsk

Produktdetaljer

ISBN
9789811927171
Publisert
2023-10-22
Utgiver
Springer Verlag, Singapore
Høyde
235 mm
Bredde
155 mm
Aldersnivå
Upper undergraduate, P, 06
Språk
Product language
Engelsk
Format
Product format
Heftet
Antall sider
9

Forfatter
Hanada, Masanori
Matsuura, So

MCMC from Scratch A Practical Introduction to Markov Chain Monte Carlo

Hanada, Masanori Matsuura, So
Heftet / 2023 / Engelsk
Hanada, Masanori Matsuura, So
Heftet / 2023 / Engelsk
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This textbook explains the fundamentals of Markov Chain Monte Carlo (MCMC) without assuming advanced knowledge of mathematics and programming. 2, which introduces readers to the Monte Carlo algorithm and highlights the advantages of MCMC, Chap.

Les mer
This textbook explains the fundamentals of Markov Chain Monte Carlo (MCMC) without assuming advanced knowledge of mathematics and programming. MCMC is a powerful technique that can be used to integrate complicated functions or to handle complicated probability distributions. MCMC is frequently used in diverse fields where statistical methods are important – e.g. Bayesian statistics, quantum physics, machine learning, computer science, computational biology, and mathematical economics. This book aims to equip readers with a sound understanding of MCMC and enable them to write simulation codes by themselves.

The content consists of six chapters. Following Chapter 2, which introduces readers to the Monte Carlo algorithm and highlights the advantages of MCMC, Chapter 3 presents the general aspects of MCMC. Chapter 4 illustrates the essence of MCMC through the simple example of the Metropolis algorithm. In turn, Chapter 5 explains the HMC algorithm, Gibbs sampling algorithm and Metropolis-Hastings algorithm, discussing their pros, cons and pitfalls. Lastly, Chapter 6 presents several applications of MCMC. Including a wealth of examples and exercises with solutions, as well as sample codes and further math topics in the Appendix, this book offers a valuable asset for students and beginners in various fields.

Les mer
Explains the fundamentals of MCMC and important algorithms without assuming advanced knowledge of math and programming Contains many examples, exercises with solutions, and codes Equips readers to write simulation codes by themselves
Les mer
GPSR Compliance The European Union's (EU) General Product Safety Regulation (GPSR) is a set of rules that requires consumer products to be safe and our obligations to ensure this. If you have any concerns about our products you can contact us on ProductSafety@springernature.com. In case Publisher is established outside the EU, the EU authorized representative is: Springer Nature Customer Service Center GmbH Europaplatz 3 69115 Heidelberg, Germany ProductSafety@springernature.com
Les mer

Relaterte produkter

This textbook explains the fundamentals of Markov Chain Monte Carlo (MCMC) without assuming advanced knowledge of mathematics and programming. 2, which introduces readers to the Monte Carlo algorithm and highlights the advantages of MCMC, Chap.

Les mer
This textbook explains the fundamentals of Markov Chain Monte Carlo (MCMC) without assuming advanced knowledge of mathematics and programming. MCMC is a powerful technique that can be used to integrate complicated functions or to handle complicated probability distributions. MCMC is frequently used in diverse fields where statistical methods are important – e.g. Bayesian statistics, quantum physics, machine learning, computer science, computational biology, and mathematical economics. This book aims to equip readers with a sound understanding of MCMC and enable them to write simulation codes by themselves.

The content consists of six chapters. Following Chapter 2, which introduces readers to the Monte Carlo algorithm and highlights the advantages of MCMC, Chapter 3 presents the general aspects of MCMC. Chapter 4 illustrates the essence of MCMC through the simple example of the Metropolis algorithm. In turn, Chapter 5 explains the HMC algorithm, Gibbs sampling algorithm and Metropolis-Hastings algorithm, discussing their pros, cons and pitfalls. Lastly, Chapter 6 presents several applications of MCMC. Including a wealth of examples and exercises with solutions, as well as sample codes and further math topics in the Appendix, this book offers a valuable asset for students and beginners in various fields.

Les mer
Explains the fundamentals of MCMC and important algorithms without assuming advanced knowledge of math and programming Contains many examples, exercises with solutions, and codes Equips readers to write simulation codes by themselves
Les mer
GPSR Compliance The European Union's (EU) General Product Safety Regulation (GPSR) is a set of rules that requires consumer products to be safe and our obligations to ensure this. If you have any concerns about our products you can contact us on ProductSafety@springernature.com. In case Publisher is established outside the EU, the EU authorized representative is: Springer Nature Customer Service Center GmbH Europaplatz 3 69115 Heidelberg, Germany ProductSafety@springernature.com
Les mer

Produktdetaljer

ISBN
9789811927171
Publisert
2023-10-22
Utgiver
Springer Verlag, Singapore
Høyde
235 mm
Bredde
155 mm
Aldersnivå
Upper undergraduate, P, 06
Språk
Product language
Engelsk
Format
Product format
Heftet
Antall sider
9

Forfatter
Hanada, Masanori
Matsuura, So

Relaterte produkter