Lower bound for the Degrees of Freedom
This function computes the lower bound for the the Degrees of Freedom of PLS with 1 component.
compute.lower.bound(X)
X |
matrix of predictor observations. |
If the decay of the eigenvalues of cor(X) is not too fast, we can
lower-bound the Degrees of Freedom of PLS with 1 component. Note that we
implicitly assume that we use scaled predictor variables to compute the PLS
solution.
bound |
logical. bound is |
lower.bound |
if bound is TRUE, this is the lower bound, otherwise, it is set to -1 |
Nicole Kraemer
Kraemer, N., Sugiyama M. (2011). "The Degrees of Freedom of Partial Least Squares Regression". Journal of the American Statistical Association 106 (494) https://www.tandfonline.com/doi/abs/10.1198/jasa.2011.tm10107
# Boston Housing data library(MASS) data(Boston) X<-Boston[,-14] my.lower<-compute.lower.bound(X)
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