000			03925nam a22005175i 4500
001			978-1-4614-3719-2
003			DE-He213
005			20140220083248.0
007			cr nn 008mamaa
008			120723s2012 xxu| s |||| 0|eng d
020			_a9781461437192 _9978-1-4614-3719-2
024	7		_a10.1007/978-1-4614-3719-2 _2doi
050		4	_aQA276-280
072		7	_aPBT _2bicssc
072		7	_aMAT029000 _2bisacsh
082	0	4	_a519.5 _223
100	1		_aAoki, Satoshi. _eauthor.
245	1	0	_aMarkov Bases in Algebraic Statistics _h[electronic resource] / _cby Satoshi Aoki, Hisayuki Hara, Akimichi Takemura.
264		1	_aNew York, NY : _bSpringer New York : _bImprint: Springer, _c2012.
300			_aXI, 298 p. 44 illus. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aSpringer Series in Statistics, _x0172-7397 ; _v199
505	0		_aExact tests for contingency tables and discrete exponential families -- Markov chain Monte Carlo methods over discrete sample space -- Toric ideals and their Gröbner bases -- Definition of Markov bases and other bases -- Structure of minimal Markov bases -- Method of distance reduction -- Symmetry of Markov bases -- Decomposable models of contingency tables -- Markov basis for no-three-factor interaction models and some other hierarchical models -- Two-way tables with structural zeros and fixed subtable sums -- Regular factorial designs with discrete response variables -- Group-wise selection models -- The set of moves connecting specific fibers -- Disclosure limitation problem and Markov basis -- Gröbner basis techniques for design of experiments -- Running Markov chain without Markov bases -- References -- Index.
520			_aAlgebraic 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 Gröbner 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. Satoshi Aoki obtained his doctoral degree from University of Tokyo in 2004 and is currently an associate professor in Graduate school of Science and Engineering, Kagoshima University. Hisayuki Hara obtained his doctoral degree from University of Tokyo in 1999 and is currently an associate professor in Faculty of Economics, Niigata University. Akimichi Takemura obtained his doctoral degree from Stanford University in 1982 and is currently a professor in Graduate School of Information Science and Technology, University of Tokyo.
650		0	_aStatistics.
650		0	_aAlgebra.
650		0	_aMathematics.
650		0	_aMathematical statistics.
650	1	4	_aStatistics.
650	2	4	_aStatistics, general.
650	2	4	_aStatistical Theory and Methods.
650	2	4	_aGeneral Algebraic Systems.
650	2	4	_aApplications of Mathematics.
700	1		_aHara, Hisayuki. _eauthor.
700	1		_aTakemura, Akimichi. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9781461437185
830		0	_aSpringer Series in Statistics, _x0172-7397 ; _v199
856	4	0	_uhttp://dx.doi.org/10.1007/978-1-4614-3719-2
912			_aZDB-2-SMA
999			_c101431 _d101431