LRsim: Low Rank Simulation
In julierennes/denoiseR: Regularized low-rank matrix estimation
Description
Usage
Arguments
Details
Value
Examples
Description
This function simulates a data set as a low-rank signal corrupted by Gaussian noise.
Usage
1
LRsim(n, p, k, SNR)
Arguments
n
integer, number of rows
p
integer, number of columns
k
integer, rank of the signal
SNR
numeric, signal to noise ratio
Details
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).
Value
X the simulated data
mu the true signal
sigma the standard deviation of the noise added to the signal
Examples
1
Xsim= LRsim(100, 30, 2, 2)
julierennes/denoiseR documentation built on July 29, 2019, 3:38 a.m.
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Description Usage Arguments Details Value Examples
Description
This function simulates a data set as a low-rank signal corrupted by Gaussian noise.
Usage
1 | LRsim(n, p, k, SNR)
|
Arguments
n |
integer, number of rows |
p |
integer, number of columns |
k |
integer, rank of the signal |
SNR |
numeric, signal to noise ratio |
Details
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).
Value
X the simulated data
mu the true signal
sigma the standard deviation of the noise added to the signal
Examples
1 | Xsim= LRsim(100, 30, 2, 2)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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