Analysis of Multivariate and High-Dimensional Data: Series Number 32 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 32) - Image 1

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Cambridge University Press Analysis of Multivariate and High-Dimensional Data: Series Number 32 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 32)

Name: Analysis of Multivariate and High-Dimensional Data: Series Number 32 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 32)
Brand: Cambridge University Press
Price: 59.99 GBP
Availability: InStock

Econometrics

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Description

'Big data' poses challenges that require both classical multivariate methods and contemporary techniques from machine learning and engineering. This modern text equips you for the new world - integrating the old and the new, fusing theory and practice and bridging the gap to statistical learning. The theoretical framework includes formal statements that set out clearly the guaranteed 'safe operating zone' for the methods and allow you to assess whether data is in the zone, or near enough. Extensive examples showcase the strengths and limitations of different methods with 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. Suitable for master's/graduate students in statistics and researchers in data-rich disciplines.

Product Specifications

Brand: Cambridge University Press
Format: hardcover
ASIN: 0521887933
Category: Books > Subjects > Business, Finance & Law > Economics > Econometrics
Domain: Amazon UK
Release Date: 02 December 2013
Listed Since: 03 March 2013

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Cambridge University Press Analysis of Multivariate and High-Dimensional Data: Series Number 32 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 32)

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