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Bayesian Missing Data Problems (English, Ming T. Tan | Guo-Liang Tian | Kai Wang Ng)
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Specifications
| Publisher | Chapman and Hall/CRC |
| Language | English |
| ISBN-13 | 9781420077490 |
| ISBN-10 | 142007749X |
| Author | Ming T. Tan | Guo-Liang Tian | Kai Wang Ng |
Product Description
About the Book
Bayesian Missing Data Problems: EM, Data Augmentation and Noniterative Computation presents solutions to missing data problems through explicit or noniterative sampling calculation of Bayesian posteriors. The methods are based on the inverse Bayes formulae discovered by one of the author in 1995. Applying the Bayesian approach to important real-world problems, the authors focus on exact numerical solutions, a conditional sampling approach via dat…
ISBN: 9781420077490
Book Insights
What You'll Learn
- ·In-depth exploration of topics covered in Bayesian Missing Data Problems
- ·Key concepts explained with clarity and practical examples
- ·Insights valuable for anyone studying or working in Chapman and Hall/CRC
Who Should Read This
Students and professionals interested in Chapman and Hall/CRC, as well as general readers looking to expand their knowledge.
Key Highlights
- ·Brand new physical book delivered across India
- ·15-day hassle-free return policy
Frequently Asked Questions
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Bayesian Missing Data Problems is available in English on GlowMirror.
Who is the author of Bayesian Missing Data Problems?
Bayesian Missing Data Problems is authored by Ming T. Tan | Guo-Liang Tian | Kai Wang Ng.
Who published Bayesian Missing Data Problems?
Bayesian Missing Data Problems is published by Chapman and Hall/CRC.
How many pages does Bayesian Missing Data Problems have?
Page count information for Bayesian Missing Data Problems is available in the specifications section of this page.
How long does it take to read Bayesian Missing Data Problems?
At an average reading speed of 250 words per minute, reading Bayesian Missing Data Problems takes a few hours to a few days depending on reading pace.
What is Bayesian Missing Data Problems about?
About the Book
Bayesian Missing Data Problems: EM, Data Augmentation and Noniterative Computation presents solutions to missing data problems through explicit or noniterative sampling calculation of Bayesian posteriors. The methods are based on the inverse Bayes formulae discovered by one of the a...
Is Bayesian Missing Data Problems suitable for beginners?
Whether Bayesian Missing Data Problems is suitable for beginners depends on your background in Chapman and Hall/CRC. Review the product description and specifications above for details on the target audience and difficulty level.
What edition is Bayesian Missing Data Problems?
Bayesian Missing Data Problems is from the Chapman and Hall/CRC edition/year. Check the specifications section for full edition details.
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