Rankings and Preferences

New Results in Weighted Correlation and Weighted Principal Component Analysis with Applications

Nonfiction, Health & Well Being, Medical, Reference, Biostatistics, Science & Nature, Mathematics, Statistics
Cover of the book Rankings and Preferences by Joaquim Pinto da Costa, Springer Berlin Heidelberg
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Author: Joaquim Pinto da Costa ISBN: 9783662483442
Publisher: Springer Berlin Heidelberg Publication: September 15, 2015
Imprint: Springer Language: English
Author: Joaquim Pinto da Costa
ISBN: 9783662483442
Publisher: Springer Berlin Heidelberg
Publication: September 15, 2015
Imprint: Springer
Language: English

This book examines in detail the correlation, more precisely the weighted correlation and applications involving rankings. A general application is the evaluation of methods to predict rankings. Others involve rankings representing human preferences to infer user preferences; the use of weighted correlation with microarray data and those in the domain of time series. In this book we present new weighted correlation coefficients and new methods of weighted principal component analysis.

We also introduce new methods of dimension reduction and clustering for time series data and describe some theoretical results on the weighted correlation coefficients in separate sections.

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

This book examines in detail the correlation, more precisely the weighted correlation and applications involving rankings. A general application is the evaluation of methods to predict rankings. Others involve rankings representing human preferences to infer user preferences; the use of weighted correlation with microarray data and those in the domain of time series. In this book we present new weighted correlation coefficients and new methods of weighted principal component analysis.

We also introduce new methods of dimension reduction and clustering for time series data and describe some theoretical results on the weighted correlation coefficients in separate sections.

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