total_variance_explained: Adjusted Total Variance by Zou. et.al.(2006)
In ipapercodes/FGSPCA: Feature Grouping and Sparse Principal Component Analysis (FGSPCA)
Description
Usage
Arguments
Value
References
Description
To calculate the Total Variance Explained by the new normalized loadings NB.
The loadings of the ordinary principal components are uncorrelated and orthogonal,
where the orthogonal property, and the uncorrelated property are satisfied together.
Usage
1
total_variance_explained(x, NB)
Arguments
x
the data matrix by n\times p. It should not be the sample covariance matrix,
nor the correlation matrix.
NB
normalized matrix of loading vectors
Value
a list of c(pev_svd, pev_tr, pev_spca, cum_svd, cum_tr, cum_spca).
References
Zou, Hui, Trevor Hastie, and Robert Tibshirani. "Sparse principal component analysis."
Journal of computational and graphical statistics 15.2 (2006): 265-286.
ipapercodes/FGSPCA documentation built on Dec. 20, 2021, 7:58 p.m.
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Description Usage Arguments Value References
Description
To calculate the Total Variance Explained by the new normalized loadings NB. The loadings of the ordinary principal components are uncorrelated and orthogonal, where the orthogonal property, and the uncorrelated property are satisfied together.
Usage
1 | total_variance_explained(x, NB)
|
Arguments
x |
the data matrix by n\times p. It should not be the sample covariance matrix, nor the correlation matrix. |
NB |
normalized matrix of loading vectors |
Value
a list of c(pev_svd, pev_tr, pev_spca, cum_svd, cum_tr, cum_spca).
References
Zou, Hui, Trevor Hastie, and Robert Tibshirani. "Sparse principal component analysis." Journal of computational and graphical statistics 15.2 (2006): 265-286.
R Package Documentation
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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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