Description Usage Arguments Value References Examples
Fitting reduced-rank ridge regression with given rank and shrinkage penalty This is a modification of rrs.fit in rrpack version 0.1-6. In order to handle extremely large q = ncol(Y), generation of a q by q matrix is avoided.
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Y |
a matrix of response (n by q) |
X |
a matrix of covariate (n by p) |
nrank |
an integer specifying the desired rank |
lambda |
tunging parameter for the ridge penalty |
coefSVD |
logical indicating the need for SVD for the coeffient matrix int the output |
S3 rrr
object, a list consisting of
coef |
coefficient of rrs |
coef.ls |
coefficient of least square |
fitted |
fitted value of rrs |
fitted.ls |
fitted value of least square |
A |
right singular matrix |
Ad |
sigular value vector |
nrank |
rank of the fitted rrr |
Mukherjee, A. and Zhu, J. (2011) Reduced rank ridge regression and its kernal extensions.
Mukherjee, A., Chen, K., Wang, N. and Zhu, J. (2015) On the degrees of freedom of reduced-rank estimators in multivariate regression. Biometrika, 102, 457–477.
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