Markov Bases in Algebraic Statistics (Paperback, 2012 ed.)

Algebraic statistics is a rapidly developing field, where ideas from statistics and algebra meet and stimulate new research directions. One of the origins of algebraic statistics is the work by Diaconis and Sturmfels in 1998 on the use of Groebner bases for constructing a connected Markov chain for performing conditional tests of a discrete exponential family. In this book we take up this topic and present a detailed summary of developments following the seminal work of Diaconis and Sturmfels. This book is intended for statisticians with minimal backgrounds in algebra. As we ourselves learned algebraic notions through working on statistical problems and collaborating with notable algebraists, we hope that this book with many practical statistical problems is useful for statisticians to start working on the field.

General

Imprint:	Springer-Verlag New York
Country of origin:	United States
Series:	Springer Series in Statistics, 199
Release date:	August 2014
First published:	2012
Authors:	Satoshi Aoki • Hisayuki Hara • Akimichi Takemura
Dimensions:	235 x 155 x 17mm (L x W x T)
Format:	Paperback
Pages:	300
Edition:	2012 ed.
ISBN-13:	978-1-4899-9909-2
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Science & Mathematics > Mathematics > Algebra > General Books > Science & Mathematics > Mathematics > Applied mathematics > General
LSN:	1-4899-9909-4
Barcode:	9781489999092

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