Algebraic statistics uses tools from algebraic geometry, commutative algebra, combinatorics, and their computational sides to address problems in statistics and its applications. The starting point for this connection is the observation that many statistical models are semialgebraic sets. The algebra/statistics connection is now over twenty years old, and this book presents the first broad introductory treatment of the subject. Along with background material in probability, algebra, and statistics, this book covers a range of topics in algebraic statistics including algebraic exponential families, likelihood inference, Fisher's exact test, bounds on entries of contingency tables, design of experiments, identifiability of hidden variable models, phylogenetic models, and model selection. With numerous examples, references, and over 150 exercises, this book is suitable for both classroom use and independent study.
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Algebraic Statistics
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Table of contents
- Cover
- Title page
- Preface
- Chapter 1. Introduction
- Chapter 2. Probability Primer
- Chapter 3. Algebra Primer
- Chapter 4. Conditional Independence
- Chapter 5. Statistics Primer
- Chapter 6. Exponential Families
- Chapter 7. Likelihood Inference
- Chapter 8. The Cone of Sufficient Statistics
- Chapter 9. Fisher’s Exact Test
- Chapter 10. Bounds on Cell Entries
- Chapter 11. Exponential Random Graph Models
- Chapter 12. Design of Experiments
- Chapter 13. Graphical Models
- Chapter 14. Hidden Variables
- Chapter 15. Phylogenetic Models
- Chapter 16. Identifiability
- Chapter 17. Model Selection and Bayesian Integrals
- Chapter 18. MAP Estimation and Parametric Inference
- Chapter 19. Finite Metric Spaces
- Bibliography
- Index
- Back Cover
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Yes, you can access Algebraic Statistics by Seth Sullivant in PDF and/or ePUB format, as well as other popular books in Mathematics & Probability & Statistics. We have over one million books available in our catalogue for you to explore.