pca: PCA
In wrathematics/pcapack: Principal Components Analysis Tools and Utilities
Description
Principal components analysis.
Usage
1
Arguments
x
The input matrix or dataframe.
retx
Return the rotated variables?
center
Center the matrix first?
scale
Scale the matrix first?
method
"svd" for svd of data matrix, or "eigcov" for eigenvalue decomposition
of the covariance matrix.
wrathematics/pcapack documentation built on May 4, 2019, 10:53 a.m.
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Description
Principal components analysis.
Usage
1 |
Arguments
x |
The input matrix or dataframe. |
retx |
Return the rotated variables? |
center |
Center the matrix first? |
scale |
Scale the matrix first? |
method |
"svd" for svd of data matrix, or "eigcov" for eigenvalue decomposition of the covariance matrix. |
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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