Analysis of Multivariate and High-Dimensional Data

Nonfiction, Science & Nature, Mathematics, Statistics, Business & Finance
Cover of the book Analysis of Multivariate and High-Dimensional Data by Inge Koch, Cambridge University Press
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Inge Koch ISBN: 9781107501768
Publisher: Cambridge University Press Publication: December 2, 2013
Imprint: Cambridge University Press Language: English
Author: Inge Koch
ISBN: 9781107501768
Publisher: Cambridge University Press
Publication: December 2, 2013
Imprint: Cambridge University Press
Language: English

'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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

'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.

More books from Cambridge University Press

Cover of the book Anxiety Disorders by Inge Koch
Cover of the book Understanding the Leitmotif by Inge Koch
Cover of the book Manufacturing Automation by Inge Koch
Cover of the book Thucydides on Politics by Inge Koch
Cover of the book American Jewry by Inge Koch
Cover of the book Living with the Enemy by Inge Koch
Cover of the book Principles of Politics by Inge Koch
Cover of the book Australian Social Policy and the Human Services by Inge Koch
Cover of the book Rethinking Race in Modern Argentina by Inge Koch
Cover of the book The Political Economy of the Small Welfare State in South Korea by Inge Koch
Cover of the book French Colonial Soldiers in German Captivity during World War II by Inge Koch
Cover of the book Connections in Discrete Mathematics by Inge Koch
Cover of the book Networks for Learning and Knowledge Creation in Biotechnology by Inge Koch
Cover of the book Plato's Natural Philosophy by Inge Koch
Cover of the book Explorations in Ancient and Modern Philosophy: Volume 2 by Inge Koch
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy