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pls (version 1.1-0)

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

32,716

Version

1.1-0

License

GPL version 2

Maintainer

Bj�rn-Helge Mevik

Last Published

September 15th, 2024

Functions in pls (1.1-0)

mvr

Partial Least Squares and Principal Component Regression
MSEP

MSEP, RMSEP and R2 of PLSR and PCR models
NIR

Multivariate Dataset of NIR Spectra
biplot.mvr

Biplots of PLSR and PCR Models.
coefplot

Plot Regression Coefficients of PLSR and PCR models
crossval

Cross-validation of PLSR and PCR models
coef.mvr

Extract Information From a Fitted PLSR or PCR Model
cvsegments

Generate segments for cross-validation
oscorespls.fit

Orthogonal scores PLSR
plot.mvr

Plot Method for MVR objects
kernelpls.fit

Kernel PLS (Dayal and MacGregor)
mvrCv

Cross-validation
msc

Multiplicative Scatter Correction
summary.mvr

Summary and Print Methods for PLSR and PCR objects
svdpc.fit

Principal Component Regression
stdize

Standardization of Data Matrices
validationplot

Validation Plots
scoreplot

Plots of Scores, Loadings and Correlation Loadings
predict.mvr

Predict Method for PLSR and PCR
predplot

Prediction Plots
sensory

Multivariate Dataset of Sensory Data
scores

Extract Scores and Loadings from PLSR and PCR Models
simpls.fit

Sijmen de Jong's SIMPLS