Bhat_mat_rlist |
Generate a list of rank-specific Bhat matrices (the coefficient of Ridge Redundancy Analysis for each parameter lambda and nrank). |
get_Bhat_comp |
Compute the components of the coefficient Bhat using SVD. |
get_lambda |
Estimate an appropriate value for the ridge penalty (lambda). |
get_rlist |
Generate rank-specific matrices by combining the left and right components. |
MSE_lambda_rank |
Compute MSE for different ranks of the coefficient Bhat and lambda. |
rdasim1 |
Generate simulated data for Ridge Redundancy Analysis (RDA). |
rdasim2 |
Generate simulated data for Ridge Redundancy Analysis (RDA). |
rrda.coef |
Calculate the Bhat matrix from the return of the 'rrda.fit' function. |
rrda.cv |
Cross-validation for Ridge Redundancy Analysis |
rrda.fit |
Calculate the coefficient Bhat by Ridge Redundancy Analysis. |
rrda.heatmap |
Heatmap of the results of cross-validation for Bhat obtained from the 'rrda.cv' function. |
rrda.plot |
Plot the results of cross-validation for Bhat obtained from the 'rrda.cv' function. |
rrda.predict |
Calculate the predicted matrix Yhat using the coefficient Bhat obtained from the 'rrda.fit' function. |
rrda.summary |
Summarize the results of cross-validation for the coefficient Bhat obtained from the 'rrda.cv' function. |
sqrt_inv_d2_lambda |
Compute the square root of the inverse of (d^2 + lambda). |
unbiased_scale |
Scale a matrix using unbiased estimators for the mean and standard deviation. |
unscale_matrices |
Unscale a matrix based on provided mean and standard deviation values. |
unscale_nested_matrices_map |
Apply unscaling to a nested list of matrices using specified mean and standard deviation values. |
Yhat_mat_rlist |
Generate a list of rank-specific Yhat matrices. |