biplot,pcaRes-method

biplot-methods

biplot.pcaRes

choices

The variables are scaled by
$lambda^scale$ and the observations are
scaled    by $lambda ^ (1-scale)$ where
<code>lambda</code> are  the singular values as computed by
<code>princomp</code>.  Normally  $0 

scale

If true, use what Gabriel (1971) refers to as a
"principal component biplot", with $lambda = 1$ and
observations scaled up by sqrt(n) and variables scaled down by
sqrt(n). Then the inner products between variables approximate
covariances and distances between observations approximate
Mahalanobis distance.

pc.biplot

optional arguments to be passed to
<code>biplot.default</code>.


Visualize two-components simultaneously


multivariate

Provides Bayesian PCA, Probabilistic PCA, Nipals PCA,
Inverse Non-Linear PCA and the conventional SVD PCA. A cluster
based method for missing value estimation is included for
comparison. BPCA, PPCA and NipalsPCA may be used to perform PCA
on incomplete data as well as for accurate missing value
estimation. A set of methods for printing and plotting the
results is also provided. All PCA methods make use of the same
data structure (pcaRes) to provide a common interface to the
PCA results. Initiated at the Max-Planck Institute for
Molecular Plant Physiology, Golm, Germany.

Henning Redestig

pcaMethods

A collection of PCA methods

biplot-methods function

The variables are scaled by
$\lambda^{scale}$ and the observations are
scaled    by $\lambda^{scale}$ where
<code>lambda</code> are  the singular values as computed by
<code>princomp</code>.  Normally  $0\le{}scale\le{}1$, and a warning will be issued if the specified 'scale' is
outside this range.

If true, use what Gabriel (1971) refers to as a
"principal component biplot", with $\lambda=1$ and
observations scaled up by sqrt(n) and variables scaled down by
sqrt(n). Then the inner products between variables approximate
covariances and distances between observations approximate
Mahalanobis distance.

biplot-methods: Plot a overlaid scores and loadings plot

Description

Usage

Arguments

Value

Details

See Also

Examples