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Bulletin of the American Mathematical Society

The Bulletin publishes expository articles on contemporary mathematical research, written in a way that gives insight to mathematicians who may not be experts in the particular topic. The Bulletin also publishes reviews of selected books in mathematics and short articles in the Mathematical Perspectives section, both by invitation only.

ISSN 1088-9485 (online) ISSN 0273-0979 (print)

The 2020 MCQ for Bulletin of the American Mathematical Society is 0.84.

What is MCQ? The Mathematical Citation Quotient (MCQ) measures journal impact by looking at citations over a five-year period. Subscribers to MathSciNet may click through for more detailed information.


Book Review

The AMS does not provide abstracts of book reviews. You may download the entire review from the links below.

MathSciNet review: 4231141
Full text of review: PDF   This review is available free of charge.
Book Information:

Author: Seth Sullivant
Title: Algebraic statistics
Additional book information: Graduate Studies in Mathematics, Vol. 194, American Mathematical Society, Providence, RI, 2018, xiii+409 pp., ISBN 978-1-4704-3517-2

References [Enhancements On Off] (What's this?)

  • Satoshi Aoki, Hisayuki Hara, and Akimichi Takemura, Markov bases in algebraic statistics, Springer Series in Statistics, Springer, New York, 2012. MR 2961912, DOI 10.1007/978-1-4614-3719-2
  • Cristiano Bocci and Luca Chiantini, An introduction to algebraic statistics with tensors, Unitext, vol. 118, Springer, Cham, 2019. La Matematica per il 3+2. MR 3969980, DOI 10.1007/978-3-030-24624-2
  • Mathias Drton, Bernd Sturmfels, and Seth Sullivant, Lectures on algebraic statistics, Oberwolfach Seminars, vol. 39, Birkhäuser Verlag, Basel, 2009. MR 2723140, DOI 10.1007/978-3-7643-8905-5
  • Judea Pearl, Causality, 2nd ed., Cambridge University Press, Cambridge, 2009. Models, reasoning, and inference. MR 2548166, DOI 10.1017/CBO9780511803161
  • Jonas Peters, Dominik Janzing, and Bernhard Schölkopf, Elements of causal inference, Adaptive Computation and Machine Learning, MIT Press, Cambridge, MA, 2017. Foundations and learning algorithms. MR 3822088
  • Giovanni Pistone, Eva Riccomagno, and Henry P. Wynn, Algebraic statistics, Monographs on Statistics and Applied Probability, vol. 89, Chapman & Hall/CRC, Boca Raton, FL, 2001. Computational commutative algebra in statistics. MR 2332740
  • Milan Studený. Conditional independence relations have no finite complete characterization, in S. Kubik and J.A. Visek, editors, Information Theory, Statistical Decision Functions and Random Processes. Transactions of the 11th Prague Conference, volume B, pages 377–396. Kluwer, Dordrecht, 1992.
  • Sumio Watanabe, Algebraic geometry and statistical learning theory, Cambridge Monographs on Applied and Computational Mathematics, vol. 25, Cambridge University Press, Cambridge, 2009. MR 2554932, DOI 10.1017/CBO9780511800474

  • Review Information:

    Reviewer: Thomas Kahle
    Affiliation: Otto-von-Guericke-Universität Magdeburg, Magdeburg, Germany
    Journal: Bull. Amer. Math. Soc. 58 (2021), 305-309
    Published electronically: February 24, 2021
    Review copyright: © Copyright 2021 American Mathematical Society