Robust Methods for Data ReductionAuthor :
Hardback
Published : Thursday 16 April 2015
Description
This book gives a non-technical overview of robust data reduction techniques, encouraging the use of these important and useful methods in practical applications. The main areas covered include principal components analysis, sparse principal component analysis, canonical correlation analysis, factor analysis, clustering, double clustering, and discriminant analysis. Using real examples, the authors show how to implement the procedures in R. The code and data for the examples are available on the books CRC Press web page.
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