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pls (version 1.0-2)

Partial Least Squares Regression (PLSR) and Principal Component Regression (PCR)

Description

Multivariate regression by partial least squares regression (PLSR) and principal components regression (PCR). This package supersedes the pls.pcr package.

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Version

Install

install.packages('pls')

Monthly Downloads

33,140

Version

1.0-2

License

GPL version 2

Maintainer

Bj�rn-Helge Mevik

Last Published

September 15th, 2024

Functions in pls (1.0-2)

cvsegments

Generate segments for cross-validation
msc

Multiplicative Scatter Correction
MSEP

MSEP, RMSEP and R2 of PLSR and PCR models
NIR

Multivariate Dataset of NIR Spectra
biplot.mvr

Biplots of PLSR and PCR Models.
coef.mvr

Extract Information From a Fitted PLSR or PCR Model
coefplot

Plot Regression Coefficients of PLSR and PCR models
crossval

Cross-validation of PLSR and PCR models
kernelpls.fit

Kernel PLS (Dayal and MacGregor)
scores

Extract Scores and Loadings from PLSR and PCR Models
predict.mvr

Predict Method for PLSR and PCR
svdpc.fit

Principal Components Regression
oscorespls.fit

Orthogonal scores PLSR
validationplot

Validation Plots
plot.mvr

Plot Method for MVR objects
predplot

Prediction Plots
summary.mvr

Summary and Print Methods for PLSR and PCR objects
mvrCv

Cross-validation
simpls.fit

Sijmen de Jong's SIMPLS
mvr

Partial Least Squares and Principal Components Regression
scoreplot

Plots of Scores and Loadings
sensory

Multivariate Dataset of Sensory Data