000			04869nam a22005295i 4500
001			978-0-387-36620-3
003			DE-He213
005			20250710083956.0
007			cr nn 008mamaa
008			100301s2006 xxu| s |||| 0|eng d
020			_a9780387366203 _a99780387366203
024	7		_a10.1007/0-387-36620-2 _2doi
082	0	4	_a519.5 _223
100	1		_aFerraty, Frédéric. _eauthor.
245	1	0	_aNonparametric Functional Data Analysis _h[recurso electrónico] : _bTheory and Practice / _cby Frédéric Ferraty, Philippe Vieu.
264		1	_aNew York, NY : _bSpringer New York, _c2006.
300			_aXX, 258 p. 29 illus. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aSpringer Series in Statistics, _x0172-7397
505	0		_aStatistical Background for Nonparametric Statistics and Functional Data -- to Functional Nonparametric Statistics -- Some Functional Datasets and Associated Statistical Problematics -- What is a Well-Adapted Space for Functional Data? -- Local Weighting of Functional Variables -- Nonparametric Prediction from Functional Data -- Functional Nonparametric Prediction Methodologies -- Some Selected Asymptotics -- Computational Issues -- Nonparametric Classification of Functional Data -- Functional Nonparametric Supervised Classification -- Functional Nonparametric Unsupervised Classification -- Nonparametric Methods for Dependent Functional Data -- Mixing, Nonparametric and Functional Statistics -- Some Selected Asymptotics -- Application to Continuous Time Processes Prediction -- Conclusions -- Small Ball Probabilities and Semi-metrics -- Some Perspectives.
520			_aModern apparatuses allow us to collect samples of functional data, mainly curves but also images. On the other hand, nonparametric statistics produces useful tools for standard data exploration. This book links these two fields of modern statistics by explaining how functional data can be studied through parameter-free statistical ideas. This book starts from theoretical foundations including functional nonparametric modeling, description of the mathematical framework, construction of the statistical methods, and statements of their asymptotic behaviors. It proceeds to computational issues including R and S-PLUS routines. Several functional datasets in chemometrics, econometrics, and pattern recognition are used to emphasize the wide scope of nonparametric functional data analysis in applied sciences. The companion Web site includes R and S-PLUS routines, command lines for reproducing examples presented in the book, and the functional datasets. Rather than set application against theory, this book is really an interface of these two features of statistics. A special effort has been made in writing this book to accommodate several levels of reading. The computational aspects are oriented toward practitioners whereas open problems emerging from this new field of statistics will attract Ph.D. students and academic researchers. Finally, this book is also accessible to graduate students starting in the area of functional statistics. Frédéric Ferraty and Philippe Vieu are both researchers in statistics at Toulouse University (France). They are co-founders and co-organizers of the working group STAPH which acquired an international reputation for functional and operatorial statistics. They are authors of many international publications in nonparametric inference as well as functional data analysis. Their scientific works are based on extensive collaborations both with academic statisticians and with scientists from other areas. They have been invited to organize special sessions on functional data in recent international conferences and to teach Ph.D. courses in various countries.
650		0	_aSTATISTICS.
650		0	_aCOMPUTER SCIENCE.
650		0	_aDISTRIBUTION (PROBABILITY THEORY).
650		0	_aMATHEMATICAL STATISTICS.
650		0	_aENVIRONMENTAL SCIENCES.
650		0	_aECONOMETRICS.
650	1	4	_aSTATISTICS.
650	2	4	_aSTATISTICAL THEORY AND METHODS.
650	2	4	_aPROBABILITY THEORY AND STOCHASTIC PROCESSES.
650	2	4	_aECONOMETRICS.
650	2	4	_aMATH. APPL. IN ENVIRONMENTAL SCIENCE.
650	2	4	_aMATH. APPLICATIONS IN GEOSCIENCES.
650	2	4	_aPROBABILITY AND STATISTICS IN COMPUTER SCIENCE.
700	1		_aVieu, Philippe. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780387303697
830		0	_aSpringer Series in Statistics, _x0172-7397
856	4	0	_uhttp://dx.doi.org/10.1007/0-387-36620-2 _zVer el texto completo en las instalaciones del CICY
912			_aZDB-2-SMA
942			_2ddc _cER
999			_c57511 _d57511