sprcomp: compute principal components using efficient svd.
In WinVector/crosspca: Cross Validated Principal Components Analysis
Description
Usage
Arguments
Value
Examples
Description
use svd package to speed up calculation.
Usage
1
sprcomp(x, k, center, scale.)
Arguments
x
matrix to perfrom principal components analysis on.
k
integer number of components to estimate.
center
logical controls centering of data.
scale.
logical controls scaling of data.
Value
svd based prcomp only up to k singular values.
Examples
1
2
WinVector/crosspca documentation built on June 24, 2020, 5:09 p.m.
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Description Usage Arguments Value Examples
Description
use svd package to speed up calculation.
Usage
1 | sprcomp(x, k, center, scale.)
|
Arguments
x |
matrix to perfrom principal components analysis on. |
k |
integer number of components to estimate. |
center |
logical controls centering of data. |
scale. |
logical controls scaling of data. |
Value
svd based prcomp only up to k singular values.
Examples
1 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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