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The Gifi system of descriptive multivariate analysis
Open accessAbstract
The Gifi system of analyzing categorical data through nonlinear varieties of classical multivariate analysis techniques is reviewed. The system is characterized by the optimal scaling of categorical variables which is implemented through alternating least squares algorithms. The main technique of homogeneity analysis is presented, along with its extensions and generalizations leading to nonmetric principal components analysis and canonical correlation analysis. Several examples are used to illustrate the methods. A brief account of stability issues and areas of applications of the techniques is also given.
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Cites
Golub, G. (2012) · doi:10.56021/9781421407944 · Cited by 34,505
Cited by
Greenacre, M., Groenen, P. J. F., Hastie, T., D’Enza, A. I., Markos, A., & Tuzhilina, E. (2022) · Nature Reviews Methods Primers · doi:10.1038/s43586-022-00184-w · Cited by 1,773
Correspondence Analysis in R, with Two- and Three-dimensional Graphics: The ca Package
c, O. N., & Greenacre, M. (2007) · Journal of Statistical Software · doi:10.18637/jss.v020.i03 · Cited by 657
Some recent developments in PLS modeling
Wold, S., Trygg, J., Berglund, A., & Antti, H. (2001) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/s0169-7439(01)00156-3 · Cited by 559
Survey of State-of-the-Art Mixed Data Clustering Algorithms
Ahmad, A., & Khan, S. S. (2019) · IEEE Access · doi:10.1109/access.2019.2903568 · Cited by 253
Multivariable Modeling Strategies
Harrell, F. E. (2015) · Springer Series in Statistics · doi:10.1007/978-3-319-19425-7_4 · Cited by 221
Metadata
- Authors
- Michailidis, G., & de Leeuw, J.
- Venue
- Statistical Science
- Publisher
- Institute of Mathematical Statistics
- Published
- 1998-11-01
- Volume
- 13
- Issue
- 4
- Pages
- 307-336
- ISSN
- 0883-4237 (ISSN-L)
- OpenAlex
- W2063059120
- Cited by
- 260
- References
- 1
- FWCI
- 10.51
- Type
- journal article
- Language
- en
- Open access
- bronze
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