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007			cr nn 008mamaa
008			150903s2013 xxu| o |||| 0|eng d
020			_a9781461482833 _99781461482833
024	7		_a10.1007/9781461482833 _2doi
035			_avtls000342444
039		9	_a201509030853 _bVLOAD _c201405050243 _dVLOAD _y201402061126 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
050		4	_aQA276-280
100	1		_aAbdi, Herve. _eeditor. _9320510
245	1	0	_aNew Perspectives in Partial Least Squares and Related Methods / _cedited by Herve Abdi, Wynne W. Chin, Vincenzo Esposito Vinzi, Giorgio Russolillo, Laura Trinchera.
264		1	_aNew York, NY : _bSpringer New York : _bImprint: Springer, _c2013.
300			_axxiii, 344 páginas 96 ilustraciones, 49 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 Proceedings in Mathematics & Statistics, _x2194-1009 ; _v56
500			_aSpringer eBooks
505	0		_aKeynotes -- Large Datasets and Genomics -- Brain Imaging -- Multiblock Data Modeling.
520			_aNew Perspectives in Partial Least Squares and Related Methods shares original, peer-reviewed research from presentations during the 2012 partial least squares methods meeting (PLS 2012). This was the 7th meeting in the series of PLS conferences and the first to take place in the USA. PLS is an abbreviation for Partial Least Squares and is also sometimes expanded as projection to latent structures. This is an approach for modeling relations between data matrices of different types of variables measured on the same set of objects. The twenty-two papers in this volume, which include three invited contributions from our keynote speakers, provide a comprehensive overview of the current state of the most advanced research related to PLS and related methods. Prominent scientists from around the world took part in PLS 2012 and their contributions covered the multiple dimensions of the partial least squares-based methods. These exciting theoretical developments ranged from partial least squares regression and correlation, component based path modeling to regularized regression and subspace visualization. In following the tradition of the six previous PLS meetings, these contributions also included a large variety of PLS approaches such as PLS metamodels, variable selection, sparse PLS regression, distance based PLS, significance vs. reliability, and non-linear PLS. Finally, these contributions applied PLS methods to data originating from the traditional econometric/economic data to genomics data, brain images, information systems, epidemiology, and chemical spectroscopy. Such a broad and comprehensive volume will also encourage new uses of PLS models in work by researchers and students in many fields.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aChin, Wynne W. _eeditor. _9320511
700	1		_aEsposito Vinzi, Vincenzo. _eeditor. _9320512
700	1		_aRussolillo, Giorgio. _eeditor. _9320513
700	1		_aTrinchera, Laura. _eeditor. _9320514
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9781461482826
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-1-4614-8283-3 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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