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MCMC from Scratch: A Practical Introduction to Markov Chain Monte Carlo, Hanada,
US $51.25
ApproximatelyS$ 65.84
Condition:
Good
A book that has been read but is in good condition. Very minimal damage to the cover including scuff marks, but no holes or tears. The dust jacket for hard covers may not be included. Binding has minimal wear. The majority of pages are undamaged with minimal creasing or tearing, minimal pencil underlining of text, no highlighting of text, no writing in margins. No missing pages.
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Located in: Carrollton, Texas, United States
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Estimated between Tue, 19 Aug and Sat, 23 Aug to 94104
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eBay item number:236195291214
Item specifics
- Condition
- ISBN
- 9789811927140
About this product
Product Identifiers
Publisher
Springer
ISBN-10
9811927146
ISBN-13
9789811927140
eBay Product ID (ePID)
23057270988
Product Key Features
Number of Pages
IX, 194 Pages
Language
English
Publication Name
Mcmc from Scratch : a Practical Introduction to Markov Chain Monte Carlo
Subject
Programming / Algorithms, Intelligence (Ai) & Semantics, Life Sciences / Biophysics, Probability & Statistics / General, Physics / Nuclear
Publication Year
2022
Type
Textbook
Subject Area
Mathematics, Computers, Science
Format
Hardcover
Dimensions
Item Weight
18.1 Oz
Item Length
9.3 in
Item Width
6.1 in
Additional Product Features
Dewey Edition
23
Number of Volumes
1 vol.
Illustrated
Yes
Dewey Decimal
519.233
Table Of Content
Chapter 1: Introduction.- Chapter 2: What is the Monte Carlo method?.- Chapter 3: General Aspects of Markov Chain Monte Carlo.- Chapter 4: Metropolis Algorithm.- Chapter 5: Other Useful Algorithms.- Chapter 6: Applications of Markov Chain Monte Carlo.
Synopsis
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 Chap. 2, which introduces readers to the Monte Carlo algorithm and highlights the advantages of MCMC, Chap. 3 presents the general aspects of MCMC. Chap. 4 illustrates the essence of MCMC through the simple example of the Metropolis algorithm. In turn, Chap. 5explains the HMC algorithm, Gibbs sampling algorithm and Metropolis-Hastings algorithm, discussing their pros, cons and pitfalls. Lastly, Chap. 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.
LC Classification Number
QA76.9.A43
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- m***k (1857)- Feedback left by buyer.Past monthVerified purchaseGood seller
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Seller feedback (38,523)
- m***k (1857)- Feedback left by buyer.Past monthVerified purchaseGood seller
- g***4 (243)- Feedback left by buyer.Past monthVerified purchaseThank you!
- y***c (12)- Feedback left by buyer.Past monthVerified purchaseArrived swiftly in great condition. Thank you! Recommended shop :)