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| as.matrix.classres | as.matrix method for classification results |
| as.matrix.ldecomp | as.matrix method for ldecomp object |
| as.matrix.plsdares | as.matrix method for PLS-DA results |
| as.matrix.plsres | as.matrix method for PLS results |
| as.matrix.regcoeffs | as.matrix method for regression coefficients class |
| as.matrix.regres | as.matrix method for regression results |
| bars | Show bars on axes |
| classify.plsda | PLS-DA classification |
| classres | Results of classification |
| crossval | Generate sequence of indices for cross-validation |
| crossval.str | String with description of cross-validation method |
| erfinv | Inverse error function |
| errorbars | Show error bars on a plot |
| getB | Low-dimensional approximation of data matrix X |
| getCalibrationData | Calibration data |
| getCalibrationData.pca | Get calibration data |
| getCalibrationData.simcam | Get calibration data |
| getClassificationPerformance | Calculation of classification performance parameters |
| getConfusionMatrix | Confusion matrix for classification results |
| getConfusionMatrix.classres | Confusion matrix for classification results |
| getMainTitle | Get main title |
| getProbabilities | Get class belonging probability |
| getProbabilities.simca | Probability of class belonging for PCA/SIMCA results |
| getRegcoeffs | Get regression coefficients |
| getRegcoeffs.pls | Regression coefficients for PLS model' |
| getSelectedComponents | Get selected components |
| getSelectedComponents.classres | Get selected components |
| getSelectivityRatio | Selectivity ratio |
| getSelectivityRatio.pls | Selectivity ratio for PLS model |
| getVIPScores | VIP scores |
| getVIPScores.pls | VIP scores for PLS model |
| imshow | show image data as an image |
| ipls | Variable selection with interval PLS |
| ipls.backward | Runs the backward iPLS algorithm |
| ipls.forward | Runs the forward iPLS algorithm |
| ldecomp | Linear decomposition of data |
| ldecomp.getDistances | Residuals distances for linear decomposition |
| ldecomp.getVariances | Explained variance for linear decomposition |
| ldecomp.plotLimits | Shows lines with critical limits on residuals plot |
| mda.cbind | A wrapper for cbind() method with proper set of attributes |
| mda.data2im | Convert data matrix to an image |
| mda.df2mat | Convert data frame to a matrix |
| mda.exclcols | Exclude/hide columns in a dataset |
| mda.exclrows | Exclude/hide rows in a dataset |
| mda.getattr | Get data attributes |
| mda.getexclind | Get indices of excluded rows or columns |
| mda.im2data | Convert image to data matrix |
| mda.inclcols | Include/unhide the excluded columns |
| mda.inclrows | include/unhide the excluded rows |
| mda.rbind | A wrapper for rbind() method with proper set of attributes |
| mda.setattr | Set data attributes |
| mda.setimbg | Remove background pixels from image data |
| mda.show | Wrapper for show() method |
| mda.subset | A wrapper for subset() method with proper set of attributed |
| mda.t | A wrapper for t() method with proper set of attributes |
| mdaplot | Plotting function for a single set of objects |
| mdaplot.areColors | Check color values |
| mdaplot.formatValues | Format vector with numeric values |
| mdaplot.getAxesLim | Calculate axes limits |
| mdaplot.getColors | Color values for plot elements |
| mdaplot.plotAxes | Create axes plane |
| mdaplot.showColorbar | Plot colorbar |
| mdaplot.showGrid | Plot grid |
| mdaplot.showLabels | Plot labels Shows labels for data elements (points, bars) on a plot. |
| mdaplot.showLegend | Plot legend |
| mdaplot.showLines | Plot lines |
| mdaplot.showRegressionLine | Regression line for data points |
| mdaplotg | Plotting function for several sets of objects |
| mdatools | Package for Multivariate Data Analysis (Chemometrics) |
| pca | Principal Component Analysis |
| pca.cal | PCA model calibration |
| pca.crossval | Cross-validation of a PCA model |
| pca.mvreplace | Replace missing values in data |
| pca.nipals | NIPALS based PCA algorithm |
| pca.run | Runs one of the selected PCA methods |
| pca.svd | Singular Values Decomposition based PCA algorithm |
| pcares | Results of PCA decomposition |
| pellets | Image data |
| people | People data |
| pinv | Pseudo-inverse matrix |
| plot.classres | Plot function for classification results |
| plot.ipls | Overview plot for iPLS results |
| plot.pca | Model overview plot for PCA |
| plot.pcares | Plot method for PCA results object |
| plot.pls | Model overview plot for PLS |
| plot.plsda | Model overview plot for PLS-DA |
| plot.plsdares | Overview plot for PLS-DA results |
| plot.plsres | Overview plot for PLS results |
| plot.randtest | Plot for randomization test results |
| plot.regcoeffs | Regression coefficients plot |
| plot.regres | plot method for regression results |
| plot.simca | Model overview plot for SIMCA |
| plot.simcam | Model overview plot for SIMCAM |
| plot.simcamres | Model overview plot for SIMCAM results |
| plotBiplot | Biplot |
| plotBiplot.pca | PCA biplot |
| plotCooman | Cooman's plot |
| plotCooman.simcam | Cooman's plot for SIMCAM model |
| plotCooman.simcamres | Cooman's plot for SIMCAM results |
| plotCorr | Correlation plot |
| plotCorr.randtest | Correlation plot for randomization test results |
| plotCumVariance | Variance plot |
| plotCumVariance.ldecomp | Cumulative explained variance plot for linear decomposition |
| plotCumVariance.pca | Cumulative explained variance plot for PCA |
| plotDiscriminationPower | Discrimination power plot |
| plotDiscriminationPower.simcam | Discrimination power plot for SIMCAM model |
| plotExtreme | Shows extreme plot for SIMCA model |
| plotExtreme.simca | Shows extreme plot for SIMCA model |
| plotHist | Statistic histogram |
| plotHist.randtest | Histogram plot for randomization test results |
| plotLoadings | Loadings plot |
| plotLoadings.pca | Loadings plot for PCA |
| plotMisclassified | Misclassification ratio plot |
| plotMisclassified.classmodel | Misclassified ratio plot for classification model |
| plotMisclassified.classres | Misclassified ratio plot for classification results |
| plotModelDistance | Model distance plot |
| plotModelDistance.simcam | Modelling distance plot for SIMCAM model |
| plotModellingPower | Modelling power plot |
| plotModellingPower.simca | Modelling power plot for SIMCA model |
| plotModellingPower.simcam | Modelling power plot for SIMCAM model |
| plotPerformance | Classification performance plot |
| plotPerformance.classmodel | Performance plot for classification model |
| plotPerformance.classres | Performance plot for classification results |
| plotPredictions | Predictions plot |
| plotPredictions.classmodel | Predictions plot for classification model |
| plotPredictions.classres | Prediction plot for classification results |
| plotPredictions.pls | Predictions plot for PLS |
| plotPredictions.plsres | Predictions plot for PLS results |
| plotPredictions.regres | Predictions plot for regression results |
| plotProbabilities | Plot for class belonging probability |
| plotProbabilities.classres | Plot for class belonging probability |
| plotRegcoeffs | Regression coefficients plot |
| plotRegcoeffs.pls | Regression coefficient plot for PLS |
| plotResiduals | Residuals plot |
| plotResiduals.ldecomp | Residuals plot for linear decomposition |
| plotResiduals.pca | Residuals plot for PCA |
| plotResiduals.pcares | Residuals plot for PCA results |
| plotResiduals.simcam | Residuals plot for SIMCAM model |
| plotResiduals.simcamres | Residuals plot for SIMCAM results |
| plotResiduals.simcares | Residuals plot for SIMCA results |
| plotRMSE | RMSE plot |
| plotRMSE.ipls | RMSE development plot |
| plotRMSE.pls | RMSE plot for PLS |
| plotRMSE.regres | RMSE plot for regression results |
| plotScores | Scores plot |
| plotScores.ldecomp | Scores plot for linear decomposition |
| plotScores.pca | Scores plot for PCA |
| plotSelection | Selected intervals plot |
| plotSelection.ipls | iPLS performance plot |
| plotSelectivityRatio | Selectivity ratio plot |
| plotSelectivityRatio.pls | Selectivity ratio plot for PLS model |
| plotSensitivity | Sensitivity plot |
| plotSensitivity.classmodel | Sensitivity plot for classification model |
| plotSensitivity.classres | Sensitivity plot for classification results |
| plotSpecificity | Specificity plot |
| plotSpecificity.classmodel | Specificity plot for classification model |
| plotSpecificity.classres | Specificity plot for classification results |
| plotVariance | Variance plot |
| plotVariance.ldecomp | Explained variance plot for linear decomposition |
| plotVariance.pca | Explained variance plot for PCA |
| plotVariance.pls | Variance plot for PLS |
| plotVIPScores | VIP scores plot |
| plotVIPScores.pls | VIP scores plot for PLS model |
| plotXCumVariance | X cumulative variance plot |
| plotXCumVariance.pls | Cumulative explained X variance plot for PLS |
| plotXCumVariance.plsres | Explained cumulative X variance plot for PLS results |
| plotXLoadings | X loadings plot |
| plotXLoadings.pls | X loadings plot for PLS |
| plotXResiduals | X residuals plot |
| plotXResiduals.pls | X residuals plot for PLS |
| plotXResiduals.plsres | X residuals plot for PLS results |
| plotXScores | X scores plot |
| plotXScores.pls | X scores plot for PLS |
| plotXScores.plsres | X scores plot for PLS results |
| plotXVariance | X variance plot |
| plotXVariance.pls | Explained X variance plot for PLS |
| plotXVariance.plsres | Explained X variance plot for PLS results |
| plotXYLoadings | X loadings plot |
| plotXYLoadings.pls | XY loadings plot for PLS |
| plotXYScores | XY scores plot |
| plotXYScores.pls | XY scores plot for PLS |
| plotXYScores.plsres | XY scores plot for PLS results |
| plotYCumVariance | Y cumulative variance plot |
| plotYCumVariance.pls | Cumulative explained Y variance plot for PLS |
| plotYCumVariance.plsres | Explained cumulative Y variance plot for PLS results |
| plotYResiduals | Y residuals plot |
| plotYResiduals.pls | Y residuals plot for PLS |
| plotYResiduals.regres | Residuals plot for regression results |
| plotYVariance | Y variance plot |
| plotYVariance.pls | Explained Y variance plot for PLS |
| plotYVariance.plsres | Explained Y variance plot for PLS results |
| pls | Partial Least Squares regression |
| pls.cal | PLS model calibration |
| pls.calculateSelectivityRatio | Selectivity ratio calculation |
| pls.calculateVIPScores | VIP scores calculation for PLS model |
| pls.crossval | Cross-validation of a PLS model |
| pls.run | Runs selected PLS algorithm |
| pls.simpls | SIMPLS algorithm |
| plsda | Partial Least Squares Discriminant Analysis |
| plsda.cal | Calibrate PLS-DA model |
| plsda.crossval | Cross-validation of a PLS-DA model |
| plsdares | PLS-DA results |
| plsres | PLS results |
| predict.pca | PCA predictions |
| predict.pls | PLS predictions |
| predict.plsda | PLS-DA predictions |
| predict.simca | SIMCA predictions |
| predict.simcam | SIMCA multiple classes predictions |
| prep.autoscale | Autoscale values |
| prep.msc | Multiplicative Scatter Correction transformation |
| prep.norm | Normalization |
| prep.savgol | Savytzky-Golay filter |
| prep.snv | Standard Normal Variate transformation |
| print.classres | Print information about classification result object |
| print.ipls | Print method for iPLS |
| print.ldecomp | Print method for linear decomposition |
| print.pca | Print method for PCA model object |
| print.pcares | Print method for PCA results object |
| print.pls | Print method for PLS model object |
| print.plsda | Print method for PLS-DA model object |
| print.plsdares | Print method for PLS-DA results object |
| print.plsres | print method for PLS results object |
| print.randtest | Print method for randtest object |
| print.regcoeffs | print method for regression coefficients class |
| print.regres | print method for regression results object |
| print.simca | Print method for SIMCA model object |
| print.simcam | Print method for SIMCAM model object |
| print.simcamres | Print method for SIMCAM results object |
| print.simcares | Print method for SIMCA results object |
| randtest | Randomization test for PLS regression |
| regcoeffs | Regression coefficients |
| regcoeffs.getStat | Confidence intervals and p-values for regression coeffificents |
| regres | Regression results |
| regres.bias | Prediction bias |
| regres.r2 | Determination coefficient |
| regres.rmse | RMSE |
| regres.slope | Slope |
| reslim.chisq | Calculates critical limits or statistic values for Q-residuals using Chi-squared distribution |
| reslim.dd | Statistical limits for Q and T2 residuals using Data Driven approach |
| reslim.hotelling | Calculates critical limits for T2-residuals using Hotelling T2 distribution |
| reslim.jm | Calculates critical limits for Q-residuals using classic JM approach |
| selectCompNum | Select optimal number of components for a model |
| selectCompNum.pca | Select optimal number of components for PCA model |
| selectCompNum.pls | Select optimal number of components for PLS model |
| setResLimits | Set residual limits for PCA model |
| setResLimits.pca | Set statistical limits for Q and T2 residuals for PCA model |
| showPredictions | Predictions |
| showPredictions.classres | Show predicted class values |
| simca | SIMCA one-class classification |
| simca.classify | SIMCA classification |
| simca.crossval | Cross-validation of a SIMCA model |
| simcam | SIMCA multiclass classification |
| simcam.getPerformanceStatistics | Performance statistics for SIMCAM model |
| simcamres | Results of SIMCA multiclass classification |
| simcares | Results of SIMCA one-class classification @description 'simcares' is used to store results for SIMCA one-class classification. |
| simdata | Spectral data of polyaromatic hydrocarbons mixing |
| summary.classres | Summary statistics about classification result object |
| summary.ipls | Summary for iPLS results |
| summary.ldecomp | Summary statistics for linear decomposition |
| summary.pca | Summary method for PCA model object |
| summary.pcares | Summary method for PCA results object |
| summary.pls | Summary method for PLS model object |
| summary.plsda | Summary method for PLS-DA model object |
| summary.plsdares | Summary method for PLS-DA results object |
| summary.plsres | summary method for PLS results object |
| summary.randtest | Summary method for randtest object |
| summary.regcoeffs | Summary method for regcoeffs object |
| summary.regres | summary method for regression results object |
| summary.simca | Summary method for SIMCA model object |
| summary.simcam | Summary method for SIMCAM model object |
| summary.simcamres | Summary method for SIMCAM results object |
| summary.simcares | Summary method for SIMCA results object |