Online Public Access Catalogue (OPAC)
Library,Documentation and Information Science Division

“A research journal serves that narrow

borderland which separates the known from the unknown”

-P.C.Mahalanobis


Image from Google Jackets

Multiple factor analysis by example using R / Jerome Pages.

By: Material type: TextTextSeries: Chapman & Hall/CRC the R seriesPublication details: Boca Raton : CRC Press, c2015.Description: xiv, 257 p. : illustrations ; 24 cmISBN:
  • 9781482205473 (hardback)
Subject(s): DDC classification:
  • 000SA.071 23 P134
Contents:
1. Principal component analysis -- 2. Multiple correspondence analysis -- 3. Factorial analysis of mixed data -- 4. Weighting groups of variables -- 5. Comparing clouds of partial individuals -- 6. Factors common to different groups of variables -- 7. Comparing groups variables and Indscal model -- 8. Qualitative and mixed data -- 9. Multiple factor analysis and Procrustes analysis -- 10. Hierarchial multiple factor analysis -- 11. Matrix calculus and Euclidean vector space -- Bibliography -- Index.
Summary: Multiple factor analysis (MFA) enables users to analyze tables of individuals and variables in which the variables are structured into quantitative, qualitative, or mixed groups. Written by the co-developer of this methodology, Multiple Factor Analysis by Example Using R brings together the theoretical and methodological aspects of MFA. It also includes examples of applications and details of how to implement MFA using an R package (FactoMineR).
Tags from this library: No tags from this library for this title. Log in to add tags.
Holdings
Item type Current library Call number Status Date due Barcode Item holds
Books ISI Library, Kolkata 000SA.071 P134 (Browse shelf(Opens below)) Available 136784
Total holds: 0

Includes bibliographical references and index.

1. Principal component analysis --
2. Multiple correspondence analysis --
3. Factorial analysis of mixed data --
4. Weighting groups of variables --
5. Comparing clouds of partial individuals --
6. Factors common to different groups of variables --
7. Comparing groups variables and Indscal model --
8. Qualitative and mixed data --
9. Multiple factor analysis and Procrustes analysis --
10. Hierarchial multiple factor analysis --
11. Matrix calculus and Euclidean vector space --
Bibliography --
Index.

Multiple factor analysis (MFA) enables users to analyze tables of individuals and variables in which the variables are structured into quantitative, qualitative, or mixed groups. Written by the co-developer of this methodology, Multiple Factor Analysis by Example Using R brings together the theoretical and methodological aspects of MFA. It also includes examples of applications and details of how to implement MFA using an R package (FactoMineR).

There are no comments on this title.

to post a comment.
Library, Documentation and Information Science Division, Indian Statistical Institute, 203 B T Road, Kolkata 700108, INDIA
Phone no. 91-33-2575 2100, Fax no. 91-33-2578 1412, ksatpathy@isical.ac.in