# A collection of PCA methods.

## Documentation for package ‘pcaMethods’ version 1.42.0

- DESCRIPTION file.
- Overview of user guides and package vignettes; browse directory.
- Package NEWS.

## Help Pages

A B C D E F G H K L M N O P Q R S T V W

## -- A --

asExprSet | Convert pcaRes object to an expression set

## -- B --

biplot-method | Biplot for pcaRes method.
biplot.pcaRes | Plot a overlaid scores and loadings plot
bpca | Bayesian PCA Missing Value Estimator
BPCA_dostep | Do BPCA estimation step
BPCA_initmodel | Initialize BPCA model

## -- C --

center | Get the centers of the original variables...
center-method | Get the centers of the original variables...
centered | Check centering was part of the model...
centered-method | Check centering was part of the model...
checkData | Do some basic checks on a given data matrix
completeObs | Get the original data with missing values replaced with predicted...
completeObs-method | Get the original data with missing values replaced with predicted...
cvseg | Get CV segments
cvstat | Get cross-validation statistics (e...
cvstat-method | Get cross-validation statistics (e...

## -- D --

deletediagonals | Delete diagonals
derrorHierarchic | Later...
dim.pcaRes | Dimensions of a PCA model...
DModX | DModX
DModX-method | DModX

## -- E --

errorHierarchic | Later...

## -- F --

fitted-method | Fitted PCA data.
fitted.pcaRes | Extract fitted values from PCA.
forkNlpcaNet | Complete copy of nlpca net object...

## -- G --

getHierarchicIdx | Index in hiearchy...

## -- H --

helix | A helix structured toy data set

## -- K --

kEstimate | Estimate best number of Components for missing value estimation
kEstimateFast | Estimate best number of Components for missing value estimation

## -- L --

leverage | Extract leverages of a PCA model
leverage-method | Extract leverages of a PCA model
lineSearch | Line search for conjugate gradient...
linr | Linear kernel...
listPcaMethods | List PCA methods
llsImpute | LLSimpute algorithm
loadings.pcaRes | Get the loadings from a PCA model...

## -- M --

metaboliteData | A incomplete metabolite data set from an Arabidopsis coldstress experiment
metaboliteDataComplete | A complete metabolite data set from an Arabidopsis coldstress experiment
method | Get the used PCA method...
method-method | Get the used PCA method...

## -- N --

nFit | Class representation of the NLPCA neural net
nFit-class | Class representation of the NLPCA neural net
nipalsPca | NIPALS PCA
nlpca | Non-linear PCA
nlpcaNet | Class representation of the NLPCA neural net
nlpcaNet-class | Class representation of the NLPCA neural net
nmissing | Missing values...
nmissing-method | Missing values...
nni | Nearest neighbour imputation
nniRes | Class for representing a nearest neighbour imputation result
nniRes-class | Class for representing a nearest neighbour imputation result
nObs | Get the number of observations used to build the PCA model.
nObs-method | Get the number of observations used to build the PCA model.
nP | Get number of PCs...
nP-method | Get number of PCs...
nPcs | Get number of PCs.
nPcs-method | Get number of PCs.
nVar | Get the number of variables used to build the PCA model.
nVar-method | Get the number of variables used to build the PCA model.

## -- O --

optiAlgCgd | Conjugate gradient optimization...
orth | Calculate an orthonormal basis

## -- P --

pca | Perform principal component analysis
pcaMethods | pcaMethods
pcaMethods-deprecated | Deprecated methods for pcaMethods
pcaRes | Class for representing a PCA result
pcaRes-class | Class for representing a PCA result
plot.pcaRes | Plot diagnostics (screeplot)
plotPcs | Plot many side by side scores XOR loadings plots
plotR2 | R2 plot (screeplot) for PCA
ppca | Probabilistic PCA
predict-method | Predict PCA data.
predict.pcaRes | Predict values from PCA.
prep | Pre-process a matrix for PCA
print-method | Print basic info...

## -- Q --

Q2 | Cross-validation for PCA

## -- R --

R2cum | Cumulative R2 is the total ratio of variance that is being...
R2cum-method | Cumulative R2 is the total ratio of variance that is being...
repmat | Replicate and tile an array.
resid-method | Residuals of PCA data.
residuals-method | Residuals of PCA data.
residuals.pcaRes | Residuals values from a PCA model.
RnipalsPca | NIPALS PCA implemented in R
robustPca | PCA implementation based on robustSvd
robustSvd | Alternating L1 Singular Value Decomposition

## -- S --

scaled | Check if scaling was part of the PCA model...
scaled-method | Check if scaling was part of the PCA model...
scl | Get the scales (e...
scl-method | Get the scales (e...
scores.pcaRes | Get the scores from a PCA model...
sDev | Get the standard deviations of the scores (indicates their...
sDev-method | Get the standard deviations of the scores (indicates their...
show-method | Show pcaRes / nniRes objects.
showNniRes | Print a nniRes model
showPcaRes | Print/Show for pcaRes
simpleEllipse | Hotelling's T^2 Ellipse
slplot | Side by side scores and loadings plot
slplot-method | Side by side scores and loadings plot
sortFeatures | Sort the features of NLPCA object...
summary | Summary of PCA model
summary-method | Summary of PCA model
svdImpute | SVDimpute algorithm
svdPca | Perform principal component analysis using singular value decomposition

## -- T --

tempFixNas | Temporary fix for missing values

## -- V --

vector2matrices-method | Tranform the vectors of weights to matrix structure...

## -- W --

wasna | Get a matrix with indicating the elements that were missing in the...
wasna-method | Get a matrix with indicating the elements that were missing in the...
weightsAccount | Create an object that holds the weights for nlpcaNet.