Synopses & Reviews
Synopsis
Written by three acknowledged experts in a new and rapidly expanding area, Algebraic Statistics explores the application of symbolic computation and Grobner Bases to experimental design, discrete probability, and statistics. This field is an outgrowth of algebraic geometry with links to a variety of other disciplines, including reliability and information theory. With no other book available on the subject, this monograph-style introduction promises to become a landmark work likely to be referenced by both the statistical community and its "relatives" in algebra and computer science.
Synopsis
Written by pioneers in this exciting new field, Algebraic Statistics introduces the application of polynomial algebra to experimental design, discrete probability, and statistics.
It begins with an introduction to Gr bner bases and a thorough description of their applications to experimental design. A special chapter covers the binary case with new application to coherent systems in reliability and two level factorial designs. The work paves the way, in the last two chapters, for the application of computer algebra to discrete probability and statistical modelling through the important concept of an algebraic statistical model.
As the first book on the subject, Algebraic Statistics presents many opportunities for spin-off research and applications and should become a landmark work welcomed by both the statistical community and its relatives in mathematics and computer science.