000			02963nam a22003735i 4500
001			285561
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007			cr nn 008mamaa
008			150903s2013 xxu| o |||| 0|eng d
020			_a9781441909251 _99781441909251
024	7		_a10.1007/9781441909251 _2doi
035			_avtls000338141
039		9	_a201509030322 _bVLOAD _c201404300340 _dVLOAD _y201402060903 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
050		4	_aQA276-280
100	1		_aWakefield, Jon. _eautor _9313813
245	1	0	_aBayesian and Frequentist Regression Methods / _cby Jon Wakefield.
264		1	_aNew York, NY : _bSpringer New York : _bImprint: Springer, _c2013.
300			_axIx, 697 páginas 140 ilustraciones, 6 ilustraciones en color. _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		_aSpringer Series in Statistics, _x0172-7397
500			_aSpringer eBooks
505	0		_aIntroduction -- Frequentist Inference -- Bayesian Inference -- Linear Models -- Binary Data Models -- General Regression Models.
520			_aBayesian and Frequentist Regression Methods provides a modern account of both Bayesian and frequentist methods of regression analysis. Many texts cover one or the other of the approaches, but this is the most comprehensive combination of Bayesian and frequentist methods that exists in one place.  The two philosophical approaches to regression methodology are featured here as complementary techniques, with theory and data analysis providing supplementary components of the discussion. In particular, methods are illustrated using a variety of data sets. The majority of the data sets are drawn from biostatistics but the techniques are generalizable to a wide range of other disciplines. While the philosophy behind each approach is discussed, the book is not ideological in nature and an emphasis is placed on practical application. It is shown that, in many situations, careful application of the respective approaches can lead to broadly similar conclusions. To use this text, the reader requires a basic understanding of calculus and linear algebra, and introductory courses in probability and statistical theory. The book is based on the author's experience teaching a graduate sequence in regression methods. The book website contains all of the code to reproduce all of the analyses and figures contained in the book.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9781441909244
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-1-4419-0925-1 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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999			_c285561 _d285561