The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Correspondence Analysis in R, with Two- and Three-dimensional Graphics: The ca Package
Open accessAbstract
We describe an implementation of simple, multiple and joint correspondence analysis in R. The resulting package comprises two parts, one for simple correspondence analysis and one for multiple and joint correspondence analysis. Within each part, functions for computation, summaries and visualization in two and three dimensions are provided, including options to display supplementary points and perform subset analyses. Special emphasis has been put on the visualization functions that offer features such as different scaling options for biplots and three-dimensional maps using the rgl package. Graphical options include shading and sizing plot symbols for the points according to their contributions to the map and masses respectively.
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Cites
Modern Applied Statistics with S
Venables, W. N., & Ripley, B. D. (2002) · Statistics and Computing · doi:10.1007/978-0-387-21706-2 · Cited by 24,305
Theory and Applications of Correspondence Analysis.
Jolliffe, I. T., & Greenacre, M. J. (1986) · Biometrics · doi:10.2307/2531266 · Cited by 3,004
Self-citationCorrespondence Analysis in Practice
Greenacre, M. (2007) · Chapman & Hall/CRC eBooks · doi:10.1201/9781420011234 · Cited by 2,040
Self-citationMultiple Correspondence Analysis and Related Methods
(2006) · Chapman & Hall/CRC eBooks · doi:10.1201/9781420011319 · Cited by 1,029
Bouroche, J.-M., & Saporta, G. (2006) · Que sais-je ? · doi:10.3917/puf.bouro.2006.01 · Cited by 985
Correspondence Analysis in the Social Sciences.
SW, Greenacre, M., & Blasius, J. (1995) · Journal of the American Statistical Association · doi:10.2307/2291110 · Cited by 426
Self-citationThe Gifi system of descriptive multivariate analysis
Michailidis, G., & de Leeuw, J. (1998) · Statistical Science · doi:10.1214/ss/1028905828 · Cited by 260
Correspondence analysis of multivariate categorical data by weighted least-squares
Greenacre, M. J. (1988) · Biometrika · doi:10.1093/biomet/75.3.457 · Cited by 123
Self-citationTying up the loose ends in simple correspondence analysisPreprint
Greenacre, M. J. (2006) · RePEc: Research Papers in Economics · Cited by 16
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Cited by
Emotion shapes the diffusion of moralized content in social networks
Brady, W. J., Wills, J. A., Jost, J. T., Tucker, J. A., & Van Bavel, J. J. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1618923114 · Cited by 1,580
The human transcriptome across tissues and individuals
Melé, M., Ferreira, P. G., Reverter, F., DeLuca, D. S., Monlong, J., Sammeth, M., Young, T. R., Goldmann, J. M., Pervouchine, D. D., Sullivan, T. J., et al. (2015) · Science · doi:10.1126/science.aaa0355 · Cited by 1,304
Exploratory Multivariate Analysis by Example Using R
Husson, F. (2010) · CRC Press eBooks · doi:10.1201/b10345 · Cited by 435
Gomez, A., Petrzelkova, K. J., Burns, M. B., Yeoman, C. J., Amato, K. R., Vlckova, K., Modry, D., Todd, A., Jost Robinson, C. A., Remis, M. J., et al. (2016) · Cell Reports · doi:10.1016/j.celrep.2016.02.013 · Cited by 248
“Statistical Analyses All multivariate and community analyses were conducted using the ca, vegan, and labdsv packages of R (R Core Team, 2014) on the relative abundance of each taxon (Nenadic and Greenacre, 2007; Oksanen et al., 2012; Roberts, 2012).”
MethodDebono Spiteri, C., Gillis, R. E., Roffet-Salque, M., Castells Navarro, L., Guilaine, J., Manen, C., Muntoni, I. M., Saña Segui, M., Urem-Kotsou, D., Whelton, H. L., et al. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1607810113 · Cited by 142
Metadata
- Authors
- c, O. N., & Greenacre, M.
- Venue
- Journal of Statistical Software
- Publisher
- Foundation for Open Access Statistic
- Published
- 2007
- Volume
- 20
- Issue
- 3
- ISSN
- 1548-7660 (ISSN-L)
- OpenAlex
- W1885011557
- Cited by
- 657
- References
- 9
- Type
- journal article
- Language
- en
- Open access
- diamond
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