TExPosition (version 2.6.10.1)

TExPosition-package: TExPosition: Two-table analyses with via ExPosition.

Description

TExPosition is two-table ExPosition and includes discriminant methods of the singular value decomposition (SVD). The core of TExPosition is ExPosition and the svd.

Author

Questions, comments, compliments, and complaints go to Derek Beaton .

The following people are authors or contributors to TExPosition code, data, or examples:
Derek Beaton, Jenny Rieck, Cherise Chin-Fatt, Francesca Filbey, and Hervé Abdi.

Details

Package:	TExPosition
Type:	Package
Version:	2.6.10
Date:	2013-12-00
Depends:	R (>=2.15.0), prettyGraphs (>= 2.1.4), ExPosition (>= 2.0.0)
License:	GPL-2
URL:	http://www.utdallas.edu/~derekbeaton/software/ExPosition

References

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. & Williams, L.J. (2010). Barycentric discriminant analysis (BADIA). In N.J. Salkind, D.M., Dougherty, & B. Frey (Eds.): Encyclopedia of Research Design. Thousand Oaks (CA): Sage. pp. 64-75.
Abdi, H. (2007). Discriminant correspondence analysis. In N.J. Salkind (Ed.): Encyclopedia of Measurement and Statistics. Thousand Oaks (CA): Sage. pp. 270-275. Krishnan, A., Williams, L. J., McIntosh, A. R., & Abdi, H. (2011). Partial Least Squares (PLS) methods for neuroimaging: A tutorial and review. NeuroImage, 56(2), 455 -- 475.
McIntosh, A. R., & Lobaugh, N. J. (2004). Partial least squares analysis of neuroimaging data: applications and advances. Neuroimage, 23, S250--S263.

See Also

tepBADA, tepPLS, tepGPLS, tepDICA, tepPLSCA

Examples

#For more examples, see each individual function (as noted above).