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pls (version 1.2-1)

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

Description

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

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Version

Install

install.packages('pls')

Monthly Downloads

33,140

Version

1.2-1

License

GPL version 2

Maintainer

Bj�rn-Helge Mevik

Last Published

September 15th, 2024

Functions in pls (1.2-1)

validationplot

Validation Plots
predict.mvr

Predict Method for PLSR and PCR
coef.mvr

Extract Information From a Fitted PLSR or PCR Model
oscorespls.fit

Orthogonal scores PLSR
stdize

Standardization of Data Matrices
naExcludeMvr

Adjust for Missing Values
plot.mvr

Plot Method for MVR objects
biplot.mvr

Biplots of PLSR and PCR Models.
mvr

Partial Least Squares and Principal Component Regression
sensory

Multivariate Dataset of Sensory Data
simpls.fit

Sijmen de Jong's SIMPLS
crossval

Cross-validation of PLSR and PCR models
predplot

Prediction Plots
svdpc.fit

Principal Component Regression
MSEP

MSEP, RMSEP and R2 of PLSR and PCR models
coefplot

Plot Regression Coefficients of PLSR and PCR models
summary.mvr

Summary and Print Methods for PLSR and PCR objects
scoreplot

Plots of Scores, Loadings and Correlation Loadings
NIR

Multivariate Dataset of NIR Spectra
cvsegments

Generate segments for cross-validation
mvrCv

Cross-validation
kernelpls.fit

Kernel PLS (Dayal and MacGregor)
msc

Multiplicative Scatter Correction
scores

Extract Scores and Loadings from PLSR and PCR Models