Man pages for plsdof
Degrees of Freedom and Statistical Inference for Partial Least Squares Regression
| benchmark.pls | Comparison of model selection criteria for Partial Least... |
| benchmark.regression | Comparison of Partial Least Squares Regression, Principal... |
| coef.plsdof | Regression coefficients |
| compute.lower.bound | Lower bound for the Degrees of Freedom |
| dA | Derivative of normalization function |
| dnormalize | Derivative of normalization function |
| dvvtz | First derivative of the projection operator |
| first.local.minimum | Index of the first local minimum. |
| information.criteria | Information criteria |
| kernel.pls.fit | Kernel Partial Least Squares Fit |
| krylov | Krylov sequence |
| linear.pls.fit | Linear Partial Least Squares Fit |
| normalize | Normalization of vectors |
| pcr | Principal Components Regression |
| pcr.cv | Model selection for Princinpal Components regression based on... |
| pls.cv | Model selection for Partial Least Squares based on... |
| pls.dof | Computation of the Degrees of Freedom |
| plsdof-package | Degrees of Freedom and Statistical Inference for Partial... |
| pls.ic | Model selection for Partial Least Squares based on... |
| pls.model | Partial Least Squares |
| ridge.cv | Ridge Regression. |
| tr | Trace of a matrix |
| vcov.plsdof | Variance-covariance matrix |
| vvtz | Projectin operator |
