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.

A collection of PCA methods

package-ubuntu-20.04-r-4.0.5#cran#pcaMethods-1.82.0

optiAlgCgd(nlnet, trainIn, trainOut, verbose = FALSE)

<table summary="R argblock">
<tr valign="top">
<td><code>nlnet</code></td>
<td>
The nlnet
</td>
</tr>
<tr valign="top">
<td><code>trainIn</code></td>
<td>
Training data
</td>
</tr>
<tr valign="top">
<td><code>trainOut</code></td>
<td>
fitted data
</td>
</tr>
<tr valign="top">
<td><code>verbose</code></td>
<td>
logical, print messages
</td>
</tr>
</table>

Henning Redestig, Matthias Scholz

package-ubuntu-20.04-r-4.0.5#cran#pcaMethods-1.82.0#docs#optiAlgCgd

optiAlgCgd

Description

Usage

Arguments

Value

Author(s)

pcaMethods

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`nlnet`	The nlnet
`trainIn`	Training data
`trainOut`	fitted data
`verbose`	logical, print messages