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Can I read Analysis of Multivariate and High-Dimensional Data (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 32) on EtoBox?

Analysis of Multivariate and High-Dimensional Data (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 32) by Inge Koch is a nonfiction available to read on EtoBox.

What is Analysis of Multivariate and High-Dimensional Data (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 32) about?

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

Who reads Analysis of Multivariate and High-Dimensional Data (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 32)?

It is typically read by self-directed learners exploring a subject in depth.

Common subject areas: history, science, philosophy, social sciences.

Author
Inge Koch
Publisher
Cambridge University Press (Virtual Publishing)
Published
2013
Language
EN
ISBN
9781139025805
Category
nonfiction
Subjects
Mathematics, Stem

Other editions & translations

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