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YuGene (version 1.1.1)

pca.default: Principal Components Analysis from the mixOmics package

Description

Performs a principal components analysis from the pca function of the mixOmics package.

Usage

## S3 method for class 'default':
pca(X, ncomp = 2, center = TRUE, scale = FALSE,
    max.iter = 500, tol = 1e-09,\dots)

Arguments

X
a numeric matrix (or data frame) which provides the data for the principal components analysis. It can contain missing values.
ncomp
integer, if data is complete ncomp decides the number of components and associated eigenvalues to display from the pcasvd algorithm and if the data has missing values, ncomp gives the number of components to k
center
a logical value indicating whether the variables should be shifted to be zero centered. Alternately, a vector of length equal the number of columns of X can be supplied. The value is passed to sca
scale
a logical value indicating whether the variables should be scaled to have unit variance before the analysis takes place. The default is FALSE for consistency with prcomp function, but in general scaling is advisable. Al
max.iter
integer, the maximum number of iterations in the NIPALS algorithm.
tol
a positive real, the tolerance used in the NIPALS algorithm.
...
not used.

encoding

latin1

Details

see pca