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A B C D E F G H K L M N O P Q R S T V W
| asExprSet | Convert pcaRes object to an expression set |
| 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 |
| 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... |
| cvstat | Get cross-validation statistics (e... |
| cvstat-method | Get cross-validation statistics (e... |
| deletediagonals | Delete diagonals |
| derrorHierarchic | Later... |
| dim.pcaRes | Dimensions of a PCA model... |
| DModX | DModX |
| DModX-method | DModX |
| errorHierarchic | Later... |
| fitted-method | Fitted PCA data. |
| fitted.pcaRes | Extract fitted values from PCA. |
| forkNlpcaNet | Complete copy of nlpca net object... |
| getHierarchicIdx | Index in hiearchy... |
| helix | A helix structured toy data set |
| kEstimate | Estimate best number of Components for missing value estimation |
| kEstimateFast | Estimate best number of Components for missing value estimation |
| 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... |
| metaboliteData | A incomplete metabolite data set from an Arabidopsis coldstress |
| metaboliteDataComplete | A complete metabolite data set from an Arabidopsis coldstress |
| method | Get the used PCA method... |
| method-method | Get the used PCA method... |
| 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. |
| optiAlgCgd | Conjugate gradient optimization... |
| orth | Calculate an orthonormal basis |
| 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... |
| Q2 | Cross-validation for PCA |
| 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 |
| 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 |
| tempFixNas | Temporary fix for missing values |
| vector2matrices-method | Tranform the vectors of weights to matrix structure... |
| 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. |