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pls (version 2.1-0)
Partial Least Squares Regression (PLSR) and Principal Component Regression (PCR)
Description
Multivariate regression by partial least squares regression (PLSR) and principal component regression (PCR).
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Install
install.packages('pls')
Monthly Downloads
24,800
Version
2.1-0
License
GPL-2
Maintainer
Bj�rn-Helge Mevik
Last Published
September 15th, 2024
Functions in pls (2.1-0)
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biplot.mvr
Biplots of PLSR and PCR Models.
coef.mvr
Extract Information From a Fitted PLSR or PCR Model
crossval
Cross-validation of PLSR and PCR models
coefplot
Plot Regression Coefficients of PLSR and PCR models
cvsegments
Generate segments for cross-validation
mvr
Partial Least Squares and Principal Component Regression
oliveoil
Sensory and physico-chemical data of olive oils
mvrVal
MSEP, RMSEP and R2 of PLSR and PCR models
mvrCv
Cross-validation
kernelpls.fit
Kernel PLS (Dayal and MacGregor)
delete.intercept
Delete intercept from model matrix
msc
Multiplicative Scatter Correction
jack.test
Jackknife approximate t tests of regression coefficients
naExcludeMvr
Adjust for Missing Values
gasoline
Octane numbers and NIR spectra of gasoline
oscorespls.fit
Orthogonal scores PLSR
pls.options
Set or return options for the pls package
plot.mvr
Plot Method for MVR objects
predict.mvr
Predict Method for PLSR and PCR
predplot
Prediction Plots
scores
Extract Scores and Loadings from PLSR and PCR Models
simpls.fit
Sijmen de Jong's SIMPLS
summary.mvr
Summary and Print Methods for PLSR and PCR objects
scoreplot
Plots of Scores, Loadings and Correlation Loadings
stdize
Standardization of Data Matrices
widekernelpls.fit
Wide Kernel PLS (R�nnar et al.)
svdpc.fit
Principal Component Regression
validationplot
Validation Plots
var.jack
Jackknife Variance Estimates of Regression Coefficients
yarn
NIR spectra and density measurements of PET yarns