Analysis of multivariate and high-dimensional data /

Analysis of multivariate and high-dimensional data /

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Bibliographic Details
Author / Creator:	Koch, Inge, 1952-
Imprint:	New York, NY : Cambridge University Press, 2014.
Description:	xxv, 504 pages : illustrations (some color) ; 26 cm.
Language:	English
Series:	Cambridge series in statistical and probabilistic mathematics ; [37] Cambridge series on statistical and probabilistic mathematics ; 37.
Subject:	Multivariate analysis. Big data. Big data. Multivariate analysis.
Format:	Print Book
URL for this record:	http://pi.lib.uchicago.edu/1001/cat/bib/10122567

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ISBN:	9780521887939 (hardback) 0521887933 (hardback)
Notes:	Includes bibliographical references (pages 483-492) and indexes.
Summary:	"'Big data' poses challenges that require both classical multivariate methods and contemporary techniques from machine learning and engineering. This modern text integrates the two strands into a coherent treatment, drawing together theory, data, computation and recent research. The theoretical framework includes formal definitions, theorems and proofs, which clearly set out the guaranteed 'safe operating zone' for the methods and allow users to assess whether data is in or near the zone. Extensive examples showcase the strengths and limitations of different methods in a range of cases: small classical data; data from medicine, biology, marketing and finance; high-dimensional data from bioinformatics; functional data from proteomics; and simulated data. High-dimension, low-sample-size data gets special attention. Several data sets are revisited repeatedly to allow comparison of methods. Generous use of colour, algorithms, Matlab code and problem sets complete the package. The text is suitable for graduate students in statistics and researchers in data-rich disciplines"--

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Call Number:	QA278.K5935 2014
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