Ridge Redundancy Analysis for High-Dimensional Omics Data

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Documentation for package ‘rrda’ version 0.1.1

Help Pages

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.