Exposition is defined as a comprehensive explanation of an idea. With ExPosition for R, a comprehensive explanation of your data will be provided with minimal effort.
The core of ExPosition is the singular value decomposition (SVD; see: svd). The point of ExPosition is simple: to provide the user with an overview of their data that only the SVD can provide. ExPosition includes several techniques that depend on the SVD (see below for examples and functions).
| Package: | ExPosition |
| Type: | Package |
| Version: | 2.8.23 |
| Date: | 2018-12-27 |
| Depends: | R (>=2.15.0), prettyGraphs (>= 2.1.4) |
| License: | GPL-2 |
| URL: | https://github.com/derekbeaton/ExPosition-Family_OLD |
Abdi, H., and Williams, L.J. (2010). Principal component analysis. Wiley Interdisciplinary Reviews: Computational Statistics, 2, 433-459. Abdi, H. and Williams, L.J. (2010). Correspondence analysis. In N.J. Salkind, D.M., Dougherty, & B. Frey (Eds.): Encyclopedia of Research Design. Thousand Oaks (CA): Sage. pp. 267-278. Abdi, H. (2007). Singular Value Decomposition (SVD) and Generalized Singular Value Decomposition (GSVD). In N.J. Salkind (Ed.): Encyclopedia of Measurement and Statistics.Thousand Oaks (CA): Sage. pp. 907-912. Abdi, H. (2007). Metric multidimensional scaling. In N.J. Salkind (Ed.): Encyclopedia of Measurement and Statistics. Thousand Oaks (CA): Sage. pp. 598-605. Greenacre, M. J. (2007). Correspondence Analysis in Practice. Chapman and Hall. Benz<U+00E9>cri, J. P. (1979). Sur le calcul des taux d'inertie dans l'analyse d'un questionnaire. Cahiers de l'Analyse des Donn<U+00E9>es, 4, 377-378.
# NOT RUN {
#For more examples, see each individual function (as noted above).
# }
Run the code above in your browser using DataCamp Workspace