mySVD: Singular Value Decomposition (SVD) as an example of...
In mwTensor: Multi-Way Component Analysis
mySVD R Documentation
Singular Value Decomposition (SVD) as an example of user-defined matrix decomposition.
Description
The input data is assumed to be a matrix.
When algorithms of MWCAParams and CoupledMWCAParams are specified as "mySVD",
This function is called in MWCA and CoupledMWCA.
Usage
mySVD(Xn, k)
Arguments
Xn
The input matrix which has N-rows and M-columns.
k
The rank parameter (k <= min(N,M))
Value
The output matrix which has N-rows and k-columns.
Author(s)
Koki Tsuyuzaki
Examples
if(interactive()){
# Test data
matdata <- matrix(runif(10*20), nrow=10, ncol=20)
# Perform SVD
mySVD(matdata, k=3)
}
mwTensor documentation built on July 9, 2023, 6:42 p.m.
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| mySVD | R Documentation |
Singular Value Decomposition (SVD) as an example of user-defined matrix decomposition.
Description
The input data is assumed to be a matrix. When algorithms of MWCAParams and CoupledMWCAParams are specified as "mySVD", This function is called in MWCA and CoupledMWCA.
Usage
mySVD(Xn, k)
Arguments
Xn |
The input matrix which has N-rows and M-columns. |
k |
The rank parameter (k <= min(N,M)) |
Value
The output matrix which has N-rows and k-columns.
Author(s)
Koki Tsuyuzaki
Examples
if(interactive()){
# Test data
matdata <- matrix(runif(10*20), nrow=10, ncol=20)
# Perform SVD
mySVD(matdata, k=3)
}
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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