東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Rankings and preferences = new resul...

Costa, Joaquim Pinto da.

FindBook

Google Book

Amazon

博客來

Rankings and preferences = new results in weighted correlation and weighted principal component analysis with applications /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Rankings and preferences/ by Joaquim Pinto da Costa.
其他題名:	new results in weighted correlation and weighted principal component analysis with applications /
作者:	Costa, Joaquim Pinto da.
出版者:	Berlin, Heidelberg :Springer Berlin Heidelberg : : 2015.,
面頁冊數:	x, 91 p. :ill., digital ;24 cm.
內容註:	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.
Contained By:	Springer eBooks
標題:	Correlation (Statistics) -
電子資源:	http://dx.doi.org/10.1007/978-3-662-48344-2
ISBN:	9783662483442

Rankings and preferences = new results in weighted correlation and weighted principal component analysis with applications /
Costa, Joaquim Pinto da.

Rankings and preferencesnew results in weighted correlation and weighted principal component analysis with applications /[electronic resource] :by Joaquim Pinto da Costa. - Berlin, Heidelberg :Springer Berlin Heidelberg :2015. - x, 91 p. :ill., digital ;24 cm. - SpringerBriefs in statistics,2191-544X. - SpringerBriefs in statistics..

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.

ISBN: 9783662483442

Standard No.: 10.1007/978-3-662-48344-2doiSubjects--Topical Terms:

529832
Correlation (Statistics)

LC Class. No.: HA31.3

Dewey Class. No.: 519.536

Rankings and preferences = new results in weighted correlation and weighted principal component analysis with applications /
LDR:02099nmm a2200325 a 4500 001 2013568
003 DE-He213
005 20160418112934.0
006 m d
007 cr nn 008maaau
008 160518s2015 gw s 0 eng d
020 $a 9783662483442 $q (electronic bk.)
020 $a 9783662483435 $q (paper)
024 7 $a 10.1007/978-3-662-48344-2 $2 doi
035 $a 978-3-662-48344-2
040 $a GP $c GP
041 0 $a eng
050 4 $a HA31.3
072 7 $a PBT $2 bicssc
072 7 $a MAT029000 $2 bisacsh
082 0 4 $a 519.536 $2 23
090 $a HA31.3 $b .C837 2015
100 1 $a Costa, Joaquim Pinto da. $3 2163036
245 1 0 $a Rankings and preferences $h [electronic resource] : $b new results in weighted correlation and weighted principal component analysis with applications / $c by Joaquim Pinto da Costa.
260 $a Berlin, Heidelberg : $b Springer Berlin Heidelberg : $b Imprint: Springer, $c 2015.
300 $a x, 91 p. : $b ill., digital ; $c 24 cm.
490 1 $a SpringerBriefs in statistics, $x 2191-544X
505 0 $a 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.
520 $a 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.
650 0 $a Correlation (Statistics) $3 529832
650 1 4 $a Statistics. $3 517247
650 2 4 $a Statistical Theory and Methods. $3 891074
650 2 4 $a Statistics for Life Sciences, Medicine, Health Sciences. $3 891086
650 2 4 $a Biostatistics. $3 1002712
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a SpringerBriefs in statistics. $3 1565658
856 4 0 $u http://dx.doi.org/10.1007/978-3-662-48344-2
950 $a Mathematics and Statistics (Springer-11649)