Algebraic and Geometric Methods in Statistics
£125.00
- Editors:
- Paolo Gibilisco, Università degli Studi di Roma 'Tor Vergata'
- Eva Riccomagno, Università degli Studi di Genova
- Maria Piera Rogantin, Università degli Studi di Genova
- Henry P. Wynn, London School of Economics and Political Science
- Date Published: October 2009
- availability: In stock
- format: Hardback
- isbn: 9780521896191
£
125.00
Hardback
Other available formats:
eBook
Looking for an inspection copy?
This title is not currently available on inspection
-
This up-to-date account of algebraic statistics and information geometry explores the emerging connections between the two disciplines, demonstrating how they can be used in design of experiments and how they benefit our understanding of statistical models, in particular, exponential models. This book presents a new way of approaching classical statistical problems and raises scientific questions that would never have been considered without the interaction of these two disciplines. Beginning with a brief introduction to each area, using simple illustrative examples, the book then proceeds with a collection of reviews and some new results written by leading researchers in their respective fields. Part III dwells in both classical and quantum information geometry, containing surveys of key results and new material. Finally, Part IV provides examples of the interplay between algebraic statistics and information geometry. Computer code and proofs are also available online, where key examples are developed in further detail.
Read more- Chapters written by leading researchers in the field
- Includes introductory and review chapters, and a glossary of terms from algebraic geometry
- Online material develops in detail some key examples, and provides computer code, technical material and detailed proofs
Customer reviews
Not yet reviewed
Be the first to review
Review was not posted due to profanity
×Product details
- Date Published: October 2009
- format: Hardback
- isbn: 9780521896191
- length: 382 pages
- dimensions: 254 x 181 x 23 mm
- weight: 0.83kg
- contains: 30 b/w illus. 35 tables
- availability: In stock
Table of Contents
List of contributors
Frequently used notations and symbols
Preface
1. Algebraic and geometric methods in statistics P. Gibilisco, E. Riccomagno, M. P. Rogantin and H. P. Wynn
Part I. Contingency Tables:
2. Maximum likelihood estimation in latent class models S. E. Fienberg, P. Hersh, A. Rinaldo and Y. Zhou
3. Algebraic geometry of 2 x 2 contingency tables A. Slavkovic and S. E. Fienberg
4. Model selection for contingency tables with algebraic statistics A. Krampe and S. Kuhnt
5. Markov chains, quotient ideals, and connectivity Y. Chen, I. Dinwoodie and R. Yoshida
6. Algebraic category distinguishability E. Carlini and F. Rapallo
7. Algebraic complexity of MLE for bivariate missing data S. Hoşten and S. Sullivant
8. The generalized shuttle algorithm A. Dobra and S. E. Fienberg
Part II. Designed Experiments:
9. Generalised design H. Maruri-Aguilar and H. P. Wynn
10. Design of experiments and biochemical network inference R. Laubenbacher and B. Stigler
11. Replicated measurements and algebraic statistics R. Notari and E. Riccomagno
12. Indicator function and sudoku designs R. Fontana and M. P. Rogantin
13. Markov basis for design of experiments and three-level factors S. Aoki and A. Takemura
Part III. Information Geometry:
14. Non-parametric estimation R. F. Streater
15. Banach manifold of quantum states R. F. Streater
16. On quantum information manifolds A. Jenčová
17. Axiomatic geometries for text documents G. Lebanon
18. Exponential manifold by reproducing kernel Hilbert spaces K. Fukumizu
19. Extended exponential models D. Imparato and B. Trivellato
20. Quantum statistics and measures of quantum information F. Hansen
Part IV. Information Geometry and Algebraic Statistics:
21. Algebraic varieties vs differentiable manifolds G. Pistone
Part V. On-Line Supplements: Coloured Figures for Chapter 2
22. Maximum likelihood estimation in latent class models Y. Zhou
23. The generalized shuttle algorithm A. Dobra and S. E. Fienberg
24. Indicator function and sudoku designs R. Fontana and M. P. Rogantin
25. Replicated measurements and algebraic statistics R. Notari and E. Riccomagno
26. Extended exponential models D. Imparato and B. Trivellato.-
Resources for
Algebraic and Geometric Methods in Statistics
General Resources
Find resources associated with this title
Type Name Unlocked * Format Size Showing of
This title is supported by one or more locked resources. Access to locked resources is granted exclusively by Cambridge University Press to lecturers whose faculty status has been verified. To gain access to locked resources, lecturers should sign in to or register for a Cambridge user account.
Please use locked resources responsibly and exercise your professional discretion when choosing how you share these materials with your students. Other lecturers may wish to use locked resources for assessment purposes and their usefulness is undermined when the source files (for example, solution manuals or test banks) are shared online or via social networks.
Supplementary resources are subject to copyright. Lecturers are permitted to view, print or download these resources for use in their teaching, but may not change them or use them for commercial gain.
If you are having problems accessing these resources please contact lecturers@cambridge.org.
Related Books
Sorry, this resource is locked
Please register or sign in to request access. If you are having problems accessing these resources please email lecturers@cambridge.org
Register Sign in» Proceed
You are now leaving the Cambridge University Press website. Your eBook purchase and download will be completed by our partner www.ebooks.com. Please see the permission section of the www.ebooks.com catalogue page for details of the print & copy limits on our eBooks.
Continue ×Are you sure you want to delete your account?
This cannot be undone.
Thank you for your feedback which will help us improve our service.
If you requested a response, we will make sure to get back to you shortly.
×