| Autor: |
Pascal G. P. Martin, Alain Baccini, Sébastien Déjean, Ignacio González |
| Jazyk: |
angličtina |
| Rok vydání: |
2007 |
| Předmět: |
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| Zdroj: |
Journal of Statistical Software, Vol 23, Iss 12 (2007) |
| Druh dokumentu: |
article |
| ISSN: |
1548-7660 |
| Popis: |
Canonical correlations analysis (CCA) is an exploratory statistical method to highlight correlations between two data sets acquired on the same experimental units. The cancor() function in R (R Development Core Team 2007) performs the core of computations but further work was required to provide the user with additional tools to facilitate the interpretation of the results. We implemented an R package, CCA, freely available from the Comprehensive R Archive Network (CRAN, http://CRAN.R-project.org/), to develop numerical and graphical outputs and to enable the user to handle missing values. The CCA package also includes a regularized version of CCA to deal with data sets with more variables than units. Illustrations are given through the analysis of a data set coming from a nutrigenomic study in the mouse. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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