000			03920nam a22004815i 4500
001			978-0-387-73508-5
003			DE-He213
005			20250710084017.0
007			cr nn 008mamaa
008			100301s2007 xxu| s |||| 0|eng d
020			_a9780387735085 _a99780387735085
024	7		_a10.1007/978-0-387-73508-5 _2doi
082	0	4	_a519.5 _223
100	1		_aHärdle, Wolfgang. _eauthor.
245	1	0	_aMultivariate Statistics _h[recurso electrónico] : _bExercises and Solutions / _cby Wolfgang Härdle, Zdeněk Hlávka.
264		1	_aNew York, NY : _bSpringer New York, _c2007.
300			_aXIII, 368 p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_aDescriptive Techniques -- Comparison of Batches -- Multivariate Random Variables -- A Short Excursion into Matrix Algebra -- Moving to Higher Dimensions -- Multivariate Distributions -- Theory of the Multinormal -- Theory of Estimation -- Hypothesis Testing -- Multivariate Techniques -- Decomposition of Data Matrices by Factors -- Principal Component Analysis -- Factor Analysis -- Cluster Analysis -- Discriminant Analysis -- Correspondence Analysis -- Canonical Correlation Analysis -- Multidimensional Scaling -- Conjoint Measurement Analysis -- Applications in Finance -- Highly Interactive, Computationally Intensive Techniques.
520			_aThe authors present tools and concepts of multivariate data analysis by means of exercises and their solutions. The first part is devoted to graphical techniques. The second part deals with multivariate random variables and presents the derivation of estimators and tests for various practical situations. The last part introduces a wide variety of exercises in applied multivariate data analysis. The book demonstrates the application of simple calculus and basic multivariate methods in real life situations. It contains altogether 234 solved exercises which can assist a university teacher in setting up a modern multivariate analysis course. All computer-based exercises are available in the R or XploRe languages. The corresponding libraries are downloadable from the Springer link web pages and from the author's home pages. Wolfgang Härdle is Professor of Statistics at Humboldt-Universität zu Berlin. He studied mathematics, computer science and physics at the University of Karlsruhe and received his Dr.rer.nat. at the University of Heidelberg. Later he had positions at Frankfurt and Bonn before he became professeur ordinaire at Université Catholique de Louvain. His current research topic is modelling of implied volatilities and the quantitative analysis of financial markets. Zdenek Hlávka studied mathematics at the Charles University in Prague and biostatistics at Limburgs Universitair Centrum in Diepenbeek. Later he held a position at Humboldt-Universität zu Berlin before he became a member of the Department of Probability and Mathematical Statistics at Charles University in Prague.
650		0	_aSTATISTICS.
650		0	_aDATA MINING.
650		0	_aCOMPUTER SCIENCE _xMATHEMATICS.
650		0	_aVISUALIZATION.
650		0	_aMATHEMATICAL STATISTICS.
650	1	4	_aSTATISTICS.
650	2	4	_aSTATISTICAL THEORY AND METHODS.
650	2	4	_aCOMPUTATIONAL MATHEMATICS AND NUMERICAL ANALYSIS.
650	2	4	_aVISUALIZATION.
650	2	4	_aDATA MINING AND KNOWLEDGE DISCOVERY.
650	2	4	_aNUMERICAL AND COMPUTATIONAL METHODS IN ENGINEERING.
700	1		_aHlávka, Zdeněk. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780387707846
856	4	0	_uhttp://dx.doi.org/10.1007/978-0-387-73508-5 _zVer el texto completo en las instalaciones del CICY
912			_aZDB-2-SMA
942			_2ddc _cER
999			_c58476 _d58476