LRsim {denoiseR} | R Documentation |
This function simulates a data set as a low-rank signal corrupted by Gaussian noise.
LRsim(n, p, k, SNR)
n |
integer, number of rows |
p |
integer, number of columns |
k |
integer, rank of the signal |
SNR |
numeric, signal to noise ratio |
A data set of size n*p and of rank k is simulated. More precisely, it is simulated as follows: A SVD is performed on a n*p matrix generated from a standard multivariate normal distribution. Then, the signal is computed using the first k singular vectors and singular values U_q D_q V_q'. The signal is scaled in such a way that the variance of each column is 1 and then a Gaussian noise with variance sigma^2 is added. The SNR is calculated as 1/ sigma sqrt(np).
X the simulated data
mu the true signal
sigma the standard deviation of the noise added to the signal
Xsim <- LRsim(100, 30, 2, 2)