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mdatools (version 0.5.1)

Multivariate data analysis for chemometrics

Description

The package implements projection based methods for preprocessing, exploring and analysis of multivariate data used in chemometrics.

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Version

Install

install.packages('mdatools')

Monthly Downloads

1,171

Version

0.5.1

License

GPL-3

Maintainer

Sergey Kucheryavskiy

Last Published

April 14th, 2014

Functions in mdatools (0.5.1)

plot.regres

plot method for regression results
plotModellingPower.simcam

Modelling power plot for SIMCAM model
erfinv

Inverse error function
plotModellingPower.simca

Modelling power plot for SIMCA model
plotSpecificity.classmodel

Specificity plot for classification model
plotVariance.pca

Explained variance plot for PCA
mdaplot

Plotting function for a single set of objects
mdaplot.plotAxes

Create axes plane
plotXScores.pls

X scores plot for PLS
getVIPScores.pls

VIP scores for PLS model
plotYResiduals

Y residuals plot
pca.svd

Singular Values Decomposition based PCA algorithm
plotCumVariance.ldecomp

Cumulative explained variance plot for linear decomposition
pls.cal

PLS model calibration
pls

Partial Least Squares regression
plsres

PLS results
print.plsdares

Print method for PLS-DA results object
plotSelectivityRatio

Selectivity ratio plot
plotSpecificity.classres

Specificity plot for classification results
print.pls

Print method for PLS model object
as.matrix.plsdares

as.matrix method for PLS-DA results
as.matrix.plsres

as.matrix method for PLS results
crossval

Generate sequence of indices for cross-validation
regcoeffs

Regression coefficients
regres.r2

Determination coefficient
getCalibrationData.pca

Get calibration data
plotPerformance.classres

Performance plot for classification results
pca.mvreplace

Replace missing values in data
summary.pca

Summary method for PCA model object
as.matrix.regres

as.matrix method for regression results
plotPredictions.pls

Predictions plot for PLS
getVIPScores

VIP scores
pca.nipals

NIPALS based PCA algorithm
pinv

Pseudo-inverse matrix
plotYResiduals.pls

Y residuals plot for PLS
mdaplot.formatValues

Format vector with numeric values
pls.simpls

SIMPLS algorithm
plotPredictions.regres

Predictions plot for regression results
plotSensitivity.classmodel

Sensitivity plot for classification model
plot.plsda

Model overview plot for PLS-DA
mdaplot.showLabels

Plot labels Shows labels for data elements (points, bars) on a plot.
plotRMSE

RMSE plot
plotSpecificity

Specificity plot
plot.simcamres

Model overview plot for SIMCAM results
mdaplot.areColors

Check color values
pca.cal

PCA model calibration
plotVariance.pls

Variance plot for PLS
plotCumVariance

Variance plot
plotSensitivity.classres

Sensitivity plot for classification results
plsdares

PLS-DA results
plotVariance

Variance plot
plot.simcam

Model overview plot for SIMCAM
pca

Principal Component Analysis
plotPerformance.classmodel

Performance plot for classification model
plotSelectivityRatio.pls

Selectivity ratio plot for PLS model
plotXLoadings

X loadings plot
simcam

SIMCA multiclass classification
plotXResiduals

X residuals plot
plotXCumVariance.pls

Cumulative explained X variance plot for PLS
plotLoadings

Loadings plot
plsda

Partial Least Squares Discriminant Analysis
plotPredictions

Predictions plot
predict.pca

PCA predictions
plotXCumVariance.plsres

Explained cumulative X variance plot for PLS results
plotVariance.ldecomp

Explained variance plot for linear decomposition
plotXLoadings.pls

X loadings plot for PLS
simcares

Results of SIMCA one-class classification
plotYResiduals.regres

Residuals plot for regression results
as.matrix.classres

as.matrix method for classification results
errorbars

Show error bars on a plot
as.matrix.regcoeffs

as.matrix method for regression coefficients class
regres.rmse

RMSE
getCalibrationData

Calibration data
print.pcares

Print method for PCA results object
as.matrix.ldecomp

as.matrix method for ldecomp object
mdatools

Package for Multivariate Data Analysis (Chemometrics)
showPredictions

Predictions
mdaplotg

Plotting function for several sets of objects
getSelectedComponents

Get selected components
plsda.crossval

Cross-validation of a PLS-DA model
plotPredictions.classmodel

Predictions plot for classification model
ldecomp.getDistances

Residuals distances for linear decomposition
summary.pcares

Summary method for PCA results object
predict.pls

PLS predictions
prep.savgol

Savytzky-Golay filter
plot.simca

Model overview plot for SIMCA
ldecomp

Linear decomposition of data
plotXYScores

XY scores plot
summary.simca

Summary method for SIMCA model object
mdaplot.showGrid

Plot grid
getClassificationPerformance

Calculation of classification performance parameters
mdaplot.showLines

Plot lines
getMainTitle

Get main title
plotCooman

Cooman's plot
pca.crossval

Cross-validation of a PCA model
plotXYScores.pls

XY scores plot for PLS
plotXCumVariance

X cumulative variance plot
plotYVariance.pls

Explained Y variance plot for PLS
prep.snv

Standard Normal Variate transformation
simdata

Spectral data of polyaromatic hydrocarbons mixing
plotYCumVariance

Y cumulative variance plot
mdaplot.getAxesLim

Calculate axes limits
plotPerformance

Classification performance plot
people

People data
plotRMSE.pls

RMSE plot for PLS
plot.pcares

Pplot method for PCA results object
plotCumVariance.pca

Cumulative explained variance plot for PCA
plotYVariance

Y variance plot
plotCooman.simcamres

Cooman's plot for SIMCAM results
plotPredictions.classres

Prediction plot for classification results
mdaplot.getColors

Color values for plot elements
plotRMSE.regres

RMSE plot for regression results
plotYCumVariance.pls

Cumulative explained Y variance plot for PLS
pls.crossval

Cross-validation of a PLS model
print.plsres

print method for PLS results object
print.simcam

Print method for SIMCAM model object
plot.pls

Model overview plot for PLS
print.ldecomp

Print method for linear decomposition
plotYVariance.plsres

Explained Y variance plot for PLS results
ldecomp.getResLimits

Statistical limits for Q2 and T2 residuals
pcares

Results of PCA decomposition
print.classres

Print information about classification result object
simca

SIMCA one-class classification
mdaplot.showColorbar

Plot colorbar
summary.plsres

summary method for PLS results object
plotYCumVariance.plsres

Explained cumulative Y variance plot for PLS results
predict.simca

SIMCA predictions
plot.classres

Plot function for classification results
prep.msc

Multiplicative Scatter Correction transformation
plotMisclassified.classmodel

Misclassified ratio plot for classification model
plotDiscriminationPower.simcam

Discrimination power plot for SIMCAM model
print.simcares

Print method for SIMCA results object
getSelectivityRatio

Selectivity ratio
plotSensitivity

Sensitivity plot
bars

Show bars on axes
plot.pca

Model overview plot for PCA
plotXScores

X scores plot
pls.calculateSelectivityRatio

Selectivity ratio calculation
plot.plsdares

Overview plot for PLS-DA results
plotRegcoeffs.pls

Regression coefficient plot for PLS
plotModellingPower

Modelling power plot
prep.autoscale

Autoscale values
predict.plsda

PLS-DA predictions
print.simcamres

Print method for SIMCAM results object
simcamres

Results of SIMCA multiclass classification
selectCompNum.pca

Select optimal number of components for PCA model
plotModelDistance

Model distance plot
simca.crossval

Cross-validation of a SIMCA model
simcam.getPerformanceStatistics

Performance statistics for SIMCAM model
plot.regcoeffs

Regression coefficients plot
simca.classify

SIMCA classification
summary.simcares

Summary method for SIMCA results object
plotDiscriminationPower

Discrimination power plot
plotResiduals.simcam

Residuals plot for SIMCAM model
plotScores.pca

Scores plot for PCA
plotVIPScores

VIP scores plot
plotXResiduals.pls

X residuals plot for PLS
summary.ldecomp

Summary statistics for linear decomposition
plotResiduals

Residuals plot
plotResiduals.ldecomp

Residuals plot for linear decomposition
pls.calculateVIPScores

VIP scores calculation for PLS model
plotXYScores.plsres

XY scores plot for PLS results
summary.plsda

Summary method for PLS-DA model object
summary.pls

Summary method for PLS model object
regres

Regression results
classres

Results of classification
summary.regres

summary method for regression results object
plotXYLoadings.pls

XY loadings plot for PLS
regres.bias

Prediction bias
regcoeffs.getStat

Confidence intervals and p-values for regression coeffificents
mdaplot.showLegend

Plot legend
mdaplot.showRegressionLine

Regression line for data points
getSelectivityRatio.pls

Selectivity ratio for PLS model
plotXVariance.pls

Explained X variance plot for PLS
plotResiduals.pca

Residuals plot for PCA
plotXVariance

X variance plot
plot.plsres

Overview plot for PLS results
print.regcoeffs

print method for regression coefficients class
plotXYLoadings

X loadings plot
selectCompNum

Select optimal number of components for a model
plotCooman.simcam

Cooman's plot for SIMCAM model
plotXScores.plsres

X scores plot for PLS results
plotRMSE.plsres

RMSE plot for PLS results
predict.simcam

SIMCA multiple classes predictions
plotRegcoeffs

Regression coefficients plot
summary.plsdares

Summary method for PLS-DA results object
regres.slope

Slope
classify.plsda

PLS-DA classification
summary.classres

Summary statistics about classification result object
getCalibrationData.simcam

Get calibration data
plotMisclassified.classres

Misclassified ratio plot for classification results
plotMisclassified

Misclassification ratio plot
plotPredictions.plsres

Predictions plot for PLS results
plotScores

Scores plot
plotResiduals.simcamres

Residuals plot for SIMCAM results
plotXResiduals.plsres

X residuals plot for PLS results
plsda.getReferenceValues

Reference values for PLS-DA
print.pca

Print method for PCA model object
ldecomp.getVariances

Explained variance for linear decomposition
plotLoadings.pca

Loadings plot for PCA
print.regres

print method for regression results object
plotResiduals.simcares

Residuals plot for SIMCA results
print.simca

Print method for SIMCA model object
print.plsda

Print method for PLS-DA model object
getSelectedComponents.classres

Get selected components
showPredictions.classres

Show predicted class values
plotModelDistance.simcam

Modelling distance plot for SIMCAM model
plotVIPScores.pls

VIP scores plot for PLS model
plotScores.ldecomp

Scores plot for linear decomposition
plotXVariance.plsres

Explained X variance plot for PLS results
selectCompNum.pls

Select optimal number of components for PLS model
summary.simcam

Summary method for SIMCAM model object
summary.simcamres

Summary method for SIMCAM results object