plsdof-package |
Degrees of Freedom and Confidence Intervals for Partial Least Squares Regression |
aic |
Akaike information criterion |
bic |
Bayesian information criterion |
coef.plsdof |
Regression coefficients |
dA |
Derivative of normalization function |
dnormalize |
Derivative of normalization function |
dvvtz |
First derivative of the projection operator |
gmdl |
Generalized minimum description length |
information.criteria |
Information criteria |
kernel.pls |
Kernel Partial Least Squares |
kernel.pls.cv |
Cross-validation for Kernel Partial Least Squares |
kernel.pls.fit |
Kernel Partial Least Squares fit |
kernel.pls.ic |
Model selection for Kernel Partial Least Squares based on information criteria |
linear.pls |
Linear Partial Least Squares |
myrange.X |
Scaling of predictor variables |
normalize |
Normalization of vectors |
plsdof |
Degrees of Freedom and Confidence Intervals for Partial Least Squares Regression |
vcov.plsdof |
Variance-covariance matrix |
vvtz |
Projectin operator |
where.max |
Compute argmax of a vector |
X2kernel |
Computation of the kernel matrix |