SPC: The sparse principal component can obtain sparse solutions of...
In SOPC: The Sparse Online Principal Component Estimation Algorithm
SPC R Documentation
The sparse principal component can obtain sparse solutions of the eigenmatrix to better explain the relationship between principal components and original variables.
Description
The sparse principal component can obtain sparse solutions of the eigenmatrix to better explain the relationship between principal components and original variables.
Usage
SPC(data, m, gamma)
Arguments
data
is a highly correlated data set
m
is the number of principal component
gamma
is a sparse parameter
Value
As,Ds
Examples
require(elasticnet)
SPC(data=PSA,m=3,gamma=0.03)
SOPC documentation built on May 31, 2023, 7:42 p.m.
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| SPC | R Documentation |
The sparse principal component can obtain sparse solutions of the eigenmatrix to better explain the relationship between principal components and original variables.
Description
The sparse principal component can obtain sparse solutions of the eigenmatrix to better explain the relationship between principal components and original variables.
Usage
SPC(data, m, gamma)
Arguments
data |
is a highly correlated data set |
m |
is the number of principal component |
gamma |
is a sparse parameter |
Value
As,Ds
Examples
require(elasticnet)
SPC(data=PSA,m=3,gamma=0.03)
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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