Bhat_mat_rlist          Generate a list of rank-specific Bhat matrices
                        (the coefficient of Ridge Redundancy Analysis
                        for each parameter lambda and nrank).
MSE_lambda_rank         Compute MSE for different ranks of the
                        coefficient Bhat and lambda.
Yhat_mat_rlist          Generate a list of rank-specific Yhat matrices.
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.
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.
rrda.top                Top feature interactions visualization with
                        rank and lambda penalty
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.
