Description Usage Arguments Value
Performs efficient eigendecomposition of an input covariance matrix based on
which principal axes that are wanted. If all axes are wanted, svd
is used. RSpectra::eigs_sym
is used if only the
highest or lowest eigenvalues with corresponding eigenvectors are requested.
1 | pca(cov_mat, axes = 1:data_dim)
|
cov_mat |
A covariance matrix. |
axes |
A vector indicating which principal axes are wanted. |
pca
returns an S3 object of class "pca". This is a list with
the following components:
vectors
A matrix with the chosen principal axes/eigenvectors as rows.
values
A vector of the corresponding eigenvalues
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