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Exploratory multivariate analysis by...

Husson, François.

Exploratory multivariate analysis by example using R[electronic resource] /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	519.53502855133
書名/作者:	Exploratory multivariate analysis by example using R/ François Husson, Sébastien Lê, Jérôme Pagès.
作者:	Husson, François.
其他作者:	Lê, Sébastien.
出版者:	Boca Raton : : CRC Press,, c2011.
面頁冊數:	1 online resource (xii, 228 p.) : : ill.
附註:	"A Chapman & Hall book".
標題:	Multivariate analysis.
標題:	R (Computer program language)
ISBN:	9781439835814 (electronic bk.)
ISBN:	1439835810 (electronic bk.)
書目註:	Includes bibliographical references and index.
內容註:	1. Principal component analysis (PCA) -- 2. Correspondence analysis (CA) -- 3. Multiple correspondence analysis (MCA) -- 4. Clustering.
摘要、提要註:	"An introduction to exploratory techniques for multivariate data analysis, this book covers the key methodology, including principal components analysis, correspondence analysis, mixed models and multiple factor analysis. The authors take a practical approach, with examples leading the discussion of the methods and lots of graphics to emphasize visualization. They present the concepts in the most intuitive way possible, keeping mathematical content to a minimum or relegating it to the appendices. The book includes examples that use real data from a range of scientific disciplines and implemented using an R package developed by the author Provided by publisher.
電子資源:	http://www.crcnetbase.com/isbn/978-1-4398-3580-7

Exploratory multivariate analysis by example using R[electronic resource] /
Husson, François.

Exploratory multivariate analysis by example using R[electronic resource] /François Husson, Sébastien Lê, Jérôme Pagès. - Boca Raton :CRC Press,c2011. - 1 online resource (xii, 228 p.) :ill. - Chapman & Hall/CRC computer science and data analysis series. - Series in computer science and data analysis..

"A Chapman & Hall book".

Includes bibliographical references and index.

1. Principal component analysis (PCA) -- 2. Correspondence analysis (CA) -- 3. Multiple correspondence analysis (MCA) -- 4. Clustering.

"An introduction to exploratory techniques for multivariate data analysis, this book covers the key methodology, including principal components analysis, correspondence analysis, mixed models and multiple factor analysis. The authors take a practical approach, with examples leading the discussion of the methods and lots of graphics to emphasize visualization. They present the concepts in the most intuitive way possible, keeping mathematical content to a minimum or relegating it to the appendices. The book includes examples that use real data from a range of scientific disciplines and implemented using an R package developed by the author Provided by publisher.

ISBN: 9781439835814 (electronic bk.)Subjects--Topical Terms:

182818
Multivariate analysis.
Index Terms--Genre/Form:

336502
Electronic books.

LC Class. No.: QA278 / .H87 2011

Dewey Class. No.: 519.53502855133

Exploratory multivariate analysis by example using R[electronic resource] /
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008 140127s2011 flua ob 001 0 eng d
020 $a 9781439835814 (electronic bk.)
020 $a 1439835810 (electronic bk.)
020 $z 9781439835807 (hbk.)
020 $z 1439835802 (hbk.)
035 $a ocn726766217
040 $a CUS $c CUS $d CUS $d NJR $d OCLCQ $d NLE
050 4 $a QA278 $b .H87 2011
082 0 0 $a 519.53502855133 $2 22
100 1 $a Husson, François. $3 558739
245 1 0 $a Exploratory multivariate analysis by example using R $h [electronic resource] / $c François Husson, Sébastien Lê, Jérôme Pagès.
260 $a Boca Raton : $b CRC Press, $c c2011.
300 $a 1 online resource (xii, 228 p.) : $b ill.
490 1 $a Chapman & Hall/CRC computer science and data analysis series
500 $a "A Chapman & Hall book".
504 $a Includes bibliographical references and index.
505 0 $a 1. Principal component analysis (PCA) -- 2. Correspondence analysis (CA) -- 3. Multiple correspondence analysis (MCA) -- 4. Clustering.
520 $a "An introduction to exploratory techniques for multivariate data analysis, this book covers the key methodology, including principal components analysis, correspondence analysis, mixed models and multiple factor analysis. The authors take a practical approach, with examples leading the discussion of the methods and lots of graphics to emphasize visualization. They present the concepts in the most intuitive way possible, keeping mathematical content to a minimum or relegating it to the appendices. The book includes examples that use real data from a range of scientific disciplines and implemented using an R package developed by the author Provided by publisher.
588 $a Description based on print version record.
650 0 $a Multivariate analysis. $3 182818
650 0 $a R (Computer program language) $3 465792
655 4 $a Electronic books. $2 local $3 336502
700 1 $a Lê, Sébastien. $3 558740
700 1 $a Pagès, Jérôme. $3 558741
830 0 $a Series in computer science and data analysis. $3 488035
856 4 0 $u http://www.crcnetbase.com/isbn/978-1-4398-3580-7

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