pca.svd: Singular Values Decomposition based PCA algorithm
In mdatools: Multivariate Data Analysis for Chemometrics
pca.svd R Documentation
Singular Values Decomposition based PCA algorithm
Description
Computes principal component space using Singular Values Decomposition
Usage
pca.svd(x, ncomp = min(ncol(x), nrow(x) - 1))
Arguments
x
a matrix with data values (preprocessed)
ncomp
number of components to calculate
Value
a list with scores, loadings and eigenvalues for the components
mdatools documentation built on Sept. 11, 2024, 7:59 p.m.
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| pca.svd | R Documentation |
Singular Values Decomposition based PCA algorithm
Description
Computes principal component space using Singular Values Decomposition
Usage
pca.svd(x, ncomp = min(ncol(x), nrow(x) - 1))
Arguments
x |
a matrix with data values (preprocessed) |
ncomp |
number of components to calculate |
Value
a list with scores, loadings and eigenvalues for the components
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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