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Algebraic Statistics

Seth Sullivant North Carolina State University, Raleigh, NC
Available Formats:
Hardcover ISBN: 978-1-4704-3517-2
Product Code: GSM/194
List Price: $83.00 MAA Member Price:$74.70
AMS Member Price: $66.40 Electronic ISBN: 978-1-4704-4980-3 Product Code: GSM/194.E List Price:$83.00
MAA Member Price: $74.70 AMS Member Price:$66.40
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List Price: $124.50 MAA Member Price:$112.05
AMS Member Price: $99.60 Click above image for expanded view Algebraic Statistics Seth Sullivant North Carolina State University, Raleigh, NC Available Formats:  Hardcover ISBN: 978-1-4704-3517-2 Product Code: GSM/194  List Price:$83.00 MAA Member Price: $74.70 AMS Member Price:$66.40
 Electronic ISBN: 978-1-4704-4980-3 Product Code: GSM/194.E
 List Price: $83.00 MAA Member Price:$74.70 AMS Member Price: $66.40 Bundle Print and Electronic Formats and Save! This product is available for purchase as a bundle. Purchasing as a bundle enables you to save on the electronic version.  List Price:$124.50 MAA Member Price: $112.05 AMS Member Price:$99.60
• Book Details

Volume: 1942018; 490 pp
MSC: Primary 62; 14; 13; 52; 60;

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.

Graduate students and researchers interested in algebraic statistics and its applications.

• Chapters
• Introduction
• Probability Primer
• Algebra Primer
• Conditional Independence
• Statistics Primer
• Exponential Families
• Likelihood Inference
• The Cone of Sufficient Statistics
• Fisher’s Exact Test
• Bounds on Cell Entries
• Exponential Random Graph Models
• Design of Experiments
• Graphical Models
• Hidden Variables
• Phylogenetic Models
• Identifiability
• Model Selection and Bayesian Integrals
• MAP Estimation and Parametric Inference
• Finite Metric Spaces

• Requests

Review Copy – for reviewers who would like to review an AMS book
Desk Copy – for instructors who have adopted an AMS textbook for a course
Examination Copy – for faculty considering an AMS textbook for a course
Permission – for use of book, eBook, or Journal content
Accessibility – to request an alternate format of an AMS title
Volume: 1942018; 490 pp
MSC: Primary 62; 14; 13; 52; 60;

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.

Graduate students and researchers interested in algebraic statistics and its applications.

• Chapters
• Introduction
• Probability Primer
• Algebra Primer
• Conditional Independence
• Statistics Primer
• Exponential Families
• Likelihood Inference
• The Cone of Sufficient Statistics
• Fisher’s Exact Test
• Bounds on Cell Entries
• Exponential Random Graph Models
• Design of Experiments
• Graphical Models
• Hidden Variables
• Phylogenetic Models
• Identifiability
• Model Selection and Bayesian Integrals
• MAP Estimation and Parametric Inference
• Finite Metric Spaces
Review Copy – for reviewers who would like to review an AMS book
Desk Copy – for instructors who have adopted an AMS textbook for a course
Examination Copy – for faculty considering an AMS textbook for a course
Permission – for use of book, eBook, or Journal content
Accessibility – to request an alternate format of an AMS title
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