000 04311nam a22004935i 4500
001 978-3-030-26006-4
003 DE-He213
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008 191122s2019 gw | s |||| 0|eng d
020 _a9783030260064
_9978-3-030-26006-4
024 7 _a10.1007/978-3-030-26006-4
_2doi
040 _cCUS
050 4 _aQA276-280
072 7 _aPBT
_2bicssc
072 7 _aMAT029000
_2bisacsh
072 7 _aPBT
_2thema
082 0 4 _a519.5
_223
100 1 _aHärdle, Wolfgang Karl.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aApplied Multivariate Statistical Analysis
_h[electronic resource] /
_cby Wolfgang Karl Härdle, Léopold Simar.
250 _a5th ed. 2019.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2019.
300 _aXII, 558 p. 443 illus., 308 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aPart I Descriptive Techniques -- 1 Comparison of Batches -- Part II Multivariate Random Variables -- 2 A Short Excursion into Matrix Algebra -- 3 Moving to Higher Dimensions -- 4 Multivariate Distributions -- 5 Theory of the Multinormal -- 6 Theory of Estimation -- 7 Hypothesis Testing -- Part III Multivariate Techniques -- 8 Regression Models -- 9 Variable Selection.-10 Decomposition of Data Matrices by Factors -- 11 Principal Components Analysis -- 12 Factor Analysis -- 13 Cluster Analysis -- 14 Discriminant Analysis -- 15 Correspondence Analysis -- 16 Canonical Correlation Analysis -- 17 Multidimensional Scaling -- 18 Conjoint Measurement Analysis -- 19 Applications in Finance -- 20 Computationally Intensive Techniques -- Part IV Appendix -- A Symbols and Notations -- B Data -- Index -- References.
520 _aThis textbook presents the tools and concepts used in multivariate data analysis in a style accessible for non-mathematicians and practitioners. All chapters include practical exercises that highlight applications in different multivariate data analysis fields, and all the examples involve high to ultra-high dimensions and represent a number of major fields in big data analysis. For this new edition, the book has been updated and extensively revised and now includes an extended chapter on cluster analysis. All solutions to the exercises are supplemented by R and MATLAB or SAS computer code and can be downloaded from the Quantlet platform. Practical exercises from this book and their solutions can also be found in the accompanying Springer book by W.K. Härdle and Z. Hlávka: Multivariate Statistics - Exercises and Solutions. The Quantlet platform, quantlet.de, quantlet.com, quantlet.org, is an integrated QuantNet environment consisting of different types of statistics-related documents and program codes. Its goal is to promote reproducibility and offer a platform for sharing validated knowledge native to the social web. QuantNet and the corresponding data-driven document-based visualization allow readers to reproduce the tables, pictures and calculations presented in this Springer book.
650 0 _aStatistics .
650 0 _aEconomics, Mathematical .
650 0 _aEconomic theory.
650 1 4 _aStatistical Theory and Methods.
_0https://scigraph.springernature.com/ontologies/product-market-codes/S11001
650 2 4 _aStatistics for Business, Management, Economics, Finance, Insurance.
_0https://scigraph.springernature.com/ontologies/product-market-codes/S17010
650 2 4 _aQuantitative Finance.
_0https://scigraph.springernature.com/ontologies/product-market-codes/M13062
650 2 4 _aEconomic Theory/Quantitative Economics/Mathematical Methods.
_0https://scigraph.springernature.com/ontologies/product-market-codes/W29000
650 2 4 _aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
_0https://scigraph.springernature.com/ontologies/product-market-codes/S17020
700 1 _aSimar, Léopold.
856 4 0 _uhttps://doi.org/10.1007/978-3-030-26006-4
912 _aZDB-2-SMA
912 _aZDB-2-SXMS
942 _cEBK
999 _c205982
_d205982