000			02686nam a22003975i 4500
001			309783
003			MX-SnUAN
005			20160429160323.0
007			cr nn 008mamaa
008			150903s2009 sz | o |||| 0|eng d
020			_a9783764389055 _99783764389055
024	7		_a10.1007/9783764389055 _2doi
035			_avtls000362994
039		9	_a201509031021 _bVLOAD _c201405070337 _dVLOAD _y201402211136 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
050		4	_aQA276-280
100	1		_aDrton, Mathias. _eautor _9350241
245	1	0	_aLectures on Algebraic Statistics / _cby Mathias Drton, Bernd Sturmfels, Seth Sullivant.
264		1	_aBasel : _bBirkhäuser Basel, _c2009.
300			_aviii, 172 páginas _brecurso en línea.
336			_atexto _btxt _2rdacontent
337			_acomputadora _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_aarchivo de texto _bPDF _2rda
490	0		_aOberwolfach Seminars ; _v39
500			_aSpringer eBooks
505	0		_aMarkov Bases -- Likelihood Inference -- Conditional Independence -- Hidden Variables -- Bayesian Integrals -- Exercises -- Open Problems.
520			_aHow does an algebraic geometer studying secant varieties further the understanding of hypothesis tests in statistics? Why would a statistician working on factor analysis raise open problems about determinantal varieties? Connections of this type are at the heart of the new field of "algebraic statistics". In this field, mathematicians and statisticians come together to solve statistical inference problems using concepts from algebraic geometry as well as related computational and combinatorial techniques. The goal of these lectures is to introduce newcomers from the different camps to algebraic statistics. The introduction will be centered around the following three observations: many important statistical models correspond to algebraic or semi-algebraic sets of parameters; the geometry of these parameter spaces determines the behaviour of widely used statistical inference procedures; computational algebraic geometry can be used to study parameter spaces and other features of statistical models.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aSturmfels, Bernd. _eautor _9302866
700	1		_aSullivant, Seth. _eautor _9300363
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9783764389048
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-3-7643-8905-5 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
942			_c14
999			_c309783 _d309783