Rankings and Preferences
Joaquim Pinto da Costa
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Description for Rankings and Preferences
Paperback. Series: SpringerBriefs in Statistics. Num Pages: 91 pages, 8 black & white illustrations, 4 colour illustrations, biography. BIC Classification: PBT; PSA. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 6. Weight in Grams: 174.
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.
Product Details
Format
Paperback
Publication date
2015
Publisher
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Germany
Number of pages
91
Condition
New
Series
SpringerBriefs in Statistics
Number of Pages
91
Place of Publication
Berlin, Germany
ISBN
9783662483435
SKU
V9783662483435
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
About Joaquim Pinto da Costa
Joaquim Pinto da Costa received his first degree in Applied Mathematics from Porto Universitiy (Portugal), his M. Sc. degree in Applied Statistics from Oxford University and his Ph.D. degree in Applied Mathematics from University of Rennes II (France). Since 199, he is Assistant Professor at the Mathematics Department of Porto University. His research interests include Statistics, Statistical Learning Theory, Pattern ... Read more
Reviews for Rankings and Preferences
“This book describes newly developed methods of weighted correlation by the author and his collaborators. … This book is useful for those who want to learn a series of studies on weighted correlations by the author and his collaborators.” (Hidehiko Kamiya, Mathematical Reviews, August, 2016)