Multivariate descriptive statistical analysis
correspondence analysis and related techniques for large matrices
by Ludovic Lebart
- 2 Want to read
- 1 Currently reading
- 1 Have read
There is an excellent chapter which relates correspondence analysis to discriminant analysis and canonical correlation analysis. Another chapter discusses cluster analysis and includes an example in which clustering is combined with correspondence analysis. First the clustering partitions the data into homogeneous groups and then the corre- spondence plot shows how the groups differ on their response. For the reader with access to a program which manipulates matrices with facility and has good plotting facilities, it should be possible to implement the procedures fairly easily without recourse to the FORTRAN program.
Check nearby libraries
Buy this book
Previews available in: English
| Edition | Availability |
|---|---|
1
Multivariate descriptive statistical analysis: correspondence analysis and related techniques for large matrices
1984, Wiley
Hardcover
in English and French
0471867438 9780471867432
|
aaaa
|
Book Details
Edition Notes
Bibliography: p. 223-228.
Translation of: Techniques de la description statistique.
Includes index.
Classifications
The Physical Object
Edition Identifiers
Work Identifiers
Source records
Work Description
This is a well-written and interesting book about techniques for displaying multi- variate data. Although the examples are applications to socioeconomic research, it is claimed that the methods can also be applied to the social sciences, medicine, biology, and geography. The primary focus is on correspondence analysis, with other techniques such as canonical correlation, discriminant analysis, and cluster analysis discussed in this context. One could conclude from the absence of exercises that the book is not intended as a text, but it certainly could be used for a class if supplemented with problems. The main prerequisite is linear algebra, but some calculus is used, too, including matrix derivatives and Lagrange multipliers. The style is informal, with techniques presented often in terms of the analysis of a particular data set, and there are no theorems presented as such. There are, however, some mathematical derivation. This is a clear, carefully written discussion of correspondence analysis, a methodology which deserves to be more widely known.
Links outside Open Library
Community Reviews (1)
Lists