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pls (version 2.2-0)
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
36,293
Version
2.2-0
License
GPL-2
Maintainer
Bj�rn-Helge Mevik
Last Published
October 20th, 2011
Functions in pls (2.2-0)
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stdize
Standardization of Data Matrices
biplot.mvr
Biplots of PLSR and PCR Models.
coefplot
Plot Regression Coefficients of PLSR and PCR models
coef.mvr
Extract Information From a Fitted PLSR or PCR Model
cvsegments
Generate segments for cross-validation
crossval
Cross-validation of PLSR and PCR models
delete.intercept
Delete intercept from model matrix
mvr
Partial Least Squares and Principal Component Regression
mvrCv
Cross-validation
kernelpls.fit
Kernel PLS (Dayal and MacGregor)
msc
Multiplicative Scatter Correction
oliveoil
Sensory and physico-chemical data of olive oils
gasoline
Octane numbers and NIR spectra of gasoline
oscorespls.fit
Orthogonal scores PLSR
plot.mvr
Plot Method for MVR objects
naExcludeMvr
Adjust for Missing Values
mvrVal
MSEP, RMSEP and R2 of PLSR and PCR models
pls.options
Set or return options for the pls package
predict.mvr
Predict Method for PLSR and PCR
scoreplot
Plots of Scores, Loadings and Correlation Loadings
summary.mvr
Summary and Print Methods for PLSR and PCR objects
var.jack
Jackknife Variance Estimates of Regression Coefficients
svdpc.fit
Principal Component Regression
scores
Extract Scores and Loadings from PLSR and PCR Models
validationplot
Validation Plots
widekernelpls.fit
Wide Kernel PLS (R�nnar et al.)
predplot
Prediction Plots
simpls.fit
Sijmen de Jong's SIMPLS
jack.test
Jackknife approximate t tests of regression coefficients
yarn
NIR spectra and density measurements of PET yarns