Description Usage Arguments Value Examples
View source: R/code_full_new.R
primePCA algorithm
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X |
an n-by-d data matrix with |
K |
the number of the principal components of interest |
V_init |
an initial estimate of the top K eigenspaces of the covariance matrix of |
thresh_sigma |
used to select the "good" rows of X to update the principal eigenspaces σ_* in the paper). |
max_iter |
maximum number of iterations of refinement |
thresh_convergence |
The algorithm is halted if the Frobenius-norm sine-theta distance between the two consecutive iterates |
thresh_als |
This is fed into |
trace.it |
report the progress if |
prob |
probability of reserving the "good" rows. |
save_file |
the location that saves the intermediate results, including |
center |
center each column of |
normalize |
normalize each column of |
a list is returned, with components V_cur
, step_cur
and loss_all
.
V_cur
is a d-by-K matrix of the top K eigenvectors. step_cur
is the number of iterations.
loss_all
is an array of the trajectory of MSE.
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