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Monte Carlo Statistical Methods (Springer Texts in Statistics)
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This new edition has been revised towards a coherent and flowing coverage of these simulation techniques, with incorporation of the most recent developments in the field. There is a more in-depth coverage of Gibbs sampling, which is now contained in three consecutive chapters.
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Detaily produktu
| Publisher | Springer |
| Publication date | July 28, 2004 |
| Edition | 2nd |
| Language | English |
| Print length | 679 pages |
| ISBN-10 | 0387212396 |
| ISBN-13 | 978-0387212395 |
| Item Weight | 2.58 pounds (1.17 kg) |
| Dimensions | 6.5 x 1.7 x 9.3 inches (16.5 x 4.3 x 23.6 cm) |
| Part of series | Springer Texts in Statistics |
Who Should Buy?
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Statistical Students
Perfect for students seeking to understand Monte Carlo methods in a comprehensive, structured way.
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Data Scientists
Beneficial for data scientists looking to apply Monte Carlo methods in practical, real-world scenarios.
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Research Professionals
Ideal for researchers needing advanced statistical methods to analyze complex problems in their fields.
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Beginners in Statistics
Not suitable for beginners without prior statistical knowledge, as concepts can be complex and demanding.
OPIS PRODUKTU
Monte Carlo Statistical Methods (Springer Texts in Statistics)
About This Item
The Monte Carlo Statistical Methods 2nd Edition is a must-have for statisticians and researchers working with Monte Carlo methods in data analysis. This comprehensive textbook provides a thorough introduction to Monte Carlo methods, with an emphasis on Markov chain Monte Carlo (MCMC) methods. The book is written as a textbook but is also highly recommended for researchers, thanks to the authors' discussion of their favorite research topics, including Monte Carlo optimization and convergence diagnostics.
It covers rapid developments in the field, making it an essential reference for statisticians interested in MCMC methods and their background. Each chapter of the book is filled with carefully worked out examples and exercises, allowing students to practice and apply the methods learned. The problems and notes at the end of each chapter further enhance the learning experience. The second edition of the book includes changes to the presentation in the early chapters and much new material related to MCMC and Gibbs sampling.
It also covers topics that have matured over the years, such as reversible jump processes, sequential MC, two-stage Gibbs sampling, and perfect sampling. Whether you are studying statistics or working in the field, the Monte Carlo Statistical Methods 2nd Edition is a valuable resource. It is suitable for advanced graduate study and is self-contained, assuming no prior knowledge of simulation or Markov chains. The book is also well-suited for self-study and serves as a valuable reference for statisticians looking to apply these techniques in their work. So, if you're interested in mastering Monte Carlo methods and expanding your statistical analysis skills, the Monte Carlo Statistical Methods 2nd Edition is the perfect choice for you.
Get your copy now and take your statistical analysis to the next level.
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Probability & Statistics Editorial Review
The Monte Carlo Statistical Methods 2nd Edition is a highly comprehensive and well-written book that provides a thorough introduction to MCMC, but requires a good background and additional references. While the book is good overall, it contains many mistakes, typos, and is sometimes misleading. The exercises provided in the book are well-designed and helpful for better understanding the material. Although the book is well-written and comprehensive, it does not handhold the reader through the math, and there are too many theories to work through, making additional references necessary. The book is recommended for those who want to understand the theory of MCMC and can work their way through the material with some difficulty. However, this is not a textbook for beginners or those who don't have a good foundation in Probability and Statistics.
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Pros
- Highly comprehensive introduction to MCMC theory
- Includes thought-provoking examples
- Provides well-designed exercises to enhance learning
- Fast delivery with high-quality physical text
Zápory
- Contains many mistakes, typos and sometimes misleading information
Product Price History
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Funkcie a výhody
- Revised edition of Monte Carlo Statistical Methods book
- Includes recent developments in the field
- More detailed coverage on Gibbs sampling
- Incorporates the most recent developments in simulation techniques
- Contains 5 newly added chapters
- Useful for students and researchers interested in learning more about MCMC methods and their background.
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