CVR-package: Canonical Variate Regression
In CVR: Canonical Variate Regression
Description
Details
Author(s)
References
See Also
Description
Perform canonical variate regression (CVR) for two sets of covariates and a univariate
response, with regularization and weight parameters tuned by cross validation.
Details
Index: This package was not yet installed at build time.
functions: cvrsolver, SparseCCA, SimulateCVR, CVR, plot.CVR.
Author(s)
Chongliang Luo, Kun Chen.
Maintainer: Chongliang Luo <chongliang.luo@uconn.edu>
References
Chongliang Luo, Jin Liu, Dipak D. Dey and Kun Chen (2016) Canonical variate regression. Accepted by Biostatistics, doi: 10.1093/biostatistics/kxw001.
Daniela M. Witten, Robert Tibshirani and Trevor Hastie (2009) A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis. Biostatistics 10(3), 515-534.
See Also
PMA.
CVR documentation built on May 2, 2019, 8:50 a.m.
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Description Details Author(s) References See Also
Description
Perform canonical variate regression (CVR) for two sets of covariates and a univariate response, with regularization and weight parameters tuned by cross validation.
Details
Index: This package was not yet installed at build time.
functions: cvrsolver, SparseCCA, SimulateCVR, CVR, plot.CVR.
Author(s)
Chongliang Luo, Kun Chen.
Maintainer: Chongliang Luo <chongliang.luo@uconn.edu>
References
Chongliang Luo, Jin Liu, Dipak D. Dey and Kun Chen (2016) Canonical variate regression. Accepted by Biostatistics, doi: 10.1093/biostatistics/kxw001.
Daniela M. Witten, Robert Tibshirani and Trevor Hastie (2009) A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis. Biostatistics 10(3), 515-534.
See Also
PMA.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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