000			04253nam a22005535i 4500
001			978-0-387-98185-7
003			DE-He213
005			20251006084433.0
007			cr nn 008mamaa
008			100301s2009 xxu| s |||| 0|eng d
020			_a9780387981857
020			_a99780387981857
024	7		_a10.1007/978-0-387-98185-7 _2doi
082	0	4	_a519.5 _223
100	1		_aRamsay, James. _eauthor.
245	1	0	_aFunctional Data Analysis with R and MATLAB _h[electronic resource] / _cby James Ramsay, Giles Hooker, Spencer Graves.
264		1	_aNew York, NY : _bSpringer New York, _c2009.
300			_bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aUse R
505	0		_ato Functional Data Analysis -- Essential Comparisons of the Matlab and R Languages -- How to Specify Basis Systems for Building Functions -- How to Build Functional Data Objects -- Smoothing: Computing Curves from Noisy Data -- Descriptions of Functional Data -- Exploring Variation: Functional Principal and Canonical Components Analysis -- Registration: Aligning Features for Samples of Curves -- Functional Linear Models for Scalar Responses -- Linear Models for Functional Responses -- Functional Models and Dynamics.
520			_aScientists often collect samples of curves and other functional observations, and develop models where parameters are also functions. This volume in the UseR! Series is aimed at a wide range of readers, and especially those who would like apply these techniques to their research problems. It complements Functional Data Analysis, Second Edition and Applied Functional Data Analysis: Methods and Case Studies by providing computer code in both the R and Matlab languages for a set of data analyses that showcase functional data analysis techniques. The authors make it easy to get up and running in new applications by adapting the code for the examples, and by being able to access the details of key functions within these pages. This book is accompanied by additional web-based support at http://www.functionaldata.org for applying existing functions and developing new ones in either language. The companion 'fda' package for R includes script files to reproduce nearly all the examples in the book including all but one of the 76 figures. Jim Ramsay is Professor Emeritus at McGill University and is an international authority on many aspects of multivariate analysis. He was President of the Statistical Society of Canada in 2002-3 and holds the Society's Gold Medal for his work in functional data analysis. His statistical work draws on his collaboration with researchers in biomechanics, chemical engineering, climatology, ecology, economics, human biology, medicine and psychology. Giles Hooker is Assistant Professor of Biological Statistics and Computational Biology at Cornell University. His research interests include statistical inference in nonlinear dynamics, machine learning and computational statistics. Spencer Graves is an engineer with a PhD in Statistics and over 15 years experience using S-Plus and R to analyze data in a broad range of applications. He has made substantive contributions to several CRAN packages including 'fda' and 'DierckxSpline.'
650		0	_aSTATISTICS.
650		0	_aDATA MINING.
650		0	_aSTATISTICAL METHODS.
650		0	_aMATHEMATICAL STATISTICS.
650		0	_aMARKETING.
650		0	_aPSYCHOMETRICS.
650	1	4	_aSTATISTICS.
650	2	4	_aSTATISTICS AND COMPUTING/STATISTICS PROGRAMS.
650	2	4	_aDATA MINING AND KNOWLEDGE DISCOVERY.
650	2	4	_aMARKETING.
650	2	4	_aBIOSTATISTICS.
650	2	4	_aPSYCHOMETRICS.
650	2	4	_aPUBLIC HEALTH/GESUNDHEITSWESEN.
700	1		_aHooker, Giles. _eauthor.
700	1		_aGraves, Spencer. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780387981840
830		0	_aUse R
856	4	0	_uhttp://dx.doi.org/10.1007/978-0-387-98185-7 _zVer el texto completo en las instalaciones del CICY
912			_aZDB-2-SMA
942			_2ddc _cER
999			_c59602 _d59602