Mathematical Geosciences

, Volume 50, Issue 3, pp 365–367 | Cite as

A Review of “Computer Age Statistical Inference” by Bradley Efron and Trevor Hastie

  • Murali Haran
Book Review

With the large number of computing-intensive statistical and machine learning methods in use today, it is easy to focus on algorithms without thinking about the principles underlying them. Professors Efron and Hastie have written a book that provides valuable insights into the statistical thinking associated with these methods, encompassing both “standard” statistical methods that have been popular and useful for a few decades, as well as cutting-edge methods that have been developed in the past few years. Given the increasing availability and importance of data and complex physical models in science, many geoscientists will find the range of topics and methods covered, as well as the discussion of foundational statistical ideas, to be very useful. The writing is interspersed with historical perspectives, which are enjoyable to read, and illuminating. The authors also frequently offer their own opinions on algorithms and methods based on their considerable expertise and their own...

Copyright information

© International Association for Mathematical Geosciences 2018

Authors and Affiliations

  1. 1.Department of StatisticsPennsylvania State UniversityUniversity ParkUSA

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