Package: pls 2.8-5

pls: Partial Least Squares and Principal Component Regression

Multivariate regression methods Partial Least Squares Regression (PLSR), Principal Component Regression (PCR) and Canonical Powered Partial Least Squares (CPPLS).

Authors:Kristian Hovde Liland [aut, cre], Bjørn-Helge Mevik [aut], Ron Wehrens [aut], Paul Hiemstra [ctb]

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pls.pdf |pls.html✨
pls/json (API)
NEWS

# Install 'pls' in R:
install.packages('pls', repos = c('https://khliland.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/khliland/pls/issues

Datasets:
  • gasoline - Octane numbers and NIR spectra of gasoline
  • mayonnaise - NIR measurements and oil types of mayonnaise
  • oliveoil - Sensory and physico-chemical data of olive oils
  • yarn - NIR spectra and density measurements of PET yarns

On CRAN:

39 exports 36 stars 7.83 score 0 dependencies 84 dependents 137 mentions 2.6k scripts 27.9k downloads

Last updated 2 days agofrom:ff1f1603b7. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 16 2024
R-4.5-winNOTESep 16 2024
R-4.5-linuxNOTESep 16 2024
R-4.4-winNOTESep 16 2024
R-4.4-macNOTESep 16 2024
R-4.3-winNOTESep 16 2024
R-4.3-macNOTESep 16 2024

Exports:coefplotcompnamescorrplotcpplscppls.fitcrossvalcvsegmentsexplvarfac2segjack.testkernelpls.fitloading.weightsloadingplotloadingsmscMSEPmvrmvrValstatsoscorespls.fitpcrpls.optionsplsrprednamespredplotpredplotXyR2respnamesRMSEPscoreplotscoresselectNcompsimpls.fitstdizesvdpc.fitvalidationplotvar.jackwidekernelpls.fitYloadingsYscores

Dependencies:

Intruction to the pls Package

Rendered frompls-manual.Rnwusingutils::Sweaveon Sep 16 2024.

Last update: 2018-08-04
Started: 2015-07-11

Readme and manuals

Help Manual

Help pageTopics
Biplots of PLSR and PCR Models.biplot.mvr
Extract Information From a Fitted PLSR or PCR Modelcoef.mvr compnames explvar fitted.mvr model.frame.mvr model.matrix.mvr prednames residuals.mvr respnames
Plot Regression Coefficients of PLSR and PCR modelscoefplot
CPPLS (Indahl et al.)cppls.fit
Cross-validation of PLSR and PCR modelscrossval
Generate segments for cross-validationcvsegments
Factor to Segmentsfac2seg
Octane numbers and NIR spectra of gasolinegasoline
Jackknife approximate t tests of regression coefficientsjack.test print.jacktest
Kernel PLS (Dayal and MacGregor)kernelpls.fit
NIR measurements and oil types of mayonnaisemayonnaise
Multiplicative Scatter Correctionmakepredictcall.msc msc predict.msc
Partial Least Squares and Principal Component Regressioncppls mvr pcr plsr
Cross-validationmvrCv
MSEP, RMSEP and R2 of PLSR and PCR modelsMSEP MSEP.mvr mvrVal mvrValstats R2 R2.mvr RMSEP RMSEP.mvr
Sensory and physico-chemical data of olive oilsoliveoil
Orthogonal scores PLSRoscorespls.fit
Plot Method for MVR objectsplot.mvr
Set or return options for the pls packagepls.options
Predict Method for PLSR and PCRpredict.mvr
Prediction Plotspredplot predplot.default predplot.mvr predplotXy
Summary and Print Methods for PLSR and PCR objectsas.data.frame.mvrVal print.mvr print.mvrVal summary.mvr
Plots of Scores, Loadings and Correlation Loadingscorrplot loadingplot loadingplot.default plot.loadings plot.scores scoreplot scoreplot.default
Extract Scores and Loadings from PLSR and PCR Modelsloading.weights loadings loadings.default scores scores.default Yloadings Yscores
Suggestions for the optimal number of components in PCR and PLSR modelsselectNcomp
Sijmen de Jong's SIMPLSsimpls.fit
Standardization of Data Matricesmakepredictcall.stdized predict.stdized stdize
Principal Component Regressionsvdpc.fit
Validation Plotsplot.mvrVal validationplot
Jackknife Variance Estimates of Regression Coefficientsvar.jack
Calculate Variance-Covariance Matrix for a Fitted Model Objectvcov.mvr
Wide Kernel PLS (Rännar et al.)widekernelpls.fit
NIR spectra and density measurements of PET yarnsyarn