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＜電子ブック＞
Rankings and Preferences : New Results in Weighted Correlation and Weighted Principal Component Analysis with Applications / by Joaquim Pinto da Costa
(SpringerBriefs in Statistics. ISSN:21915458)

版	1st ed. 2015.
出版者	(Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer)
出版年	2015
大きさ	X, 91 p. 12 illus., 4 illus. in color : online resource
著者標目	*Pinto da Costa, Joaquim author SpringerLink (Online service)
件　名	LCSH:Statistics  LCSH:Biometry FREE:Statistical Theory and Methods FREE:Biostatistics
一般注記	Introduction -- The Weighted Rank Correlation Coefficient rW -- The Weighted Rank Correlation Coefficient rW2 -- A Weighted Principal Component Analysis, WPCA1: Application to Gene Expression Data -- A Weighted Principal Component Analysis (WPCA2) for Time Series Data -- Weighted Clustering of Time Series -- Appendix -- References 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 HTTP:URL=https://doi.org/10.1007/978-3-662-48344-2

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