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pls (version 2.3-0)

Partial Least Squares and Principal Component regression

Description

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

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Version

Install

install.packages('pls')

Monthly Downloads

26,410

Version

2.3-0

License

GPL-2

Maintainer

Bj�rn-Helge Mevik

Last Published

November 28th, 2011

Functions in pls (2.3-0)

Cross-validation of PLSR and PCR models

Partial Least Squares and Principal Component Regression

Biplots of PLSR and PCR Models.

Summary and Print Methods for PLSR and PCR objects

Octane numbers and NIR spectra of gasoline

Jackknife approximate t tests of regression coefficients

Multiplicative Scatter Correction

delete.intercept

Delete intercept from model matrix

Cross-validation

Orthogonal scores PLSR

Standardization of Data Matrices

NIR spectra and density measurements of PET yarns

Kernel PLS (Dayal and MacGregor)

NIR measurements and oil types of mayonnaise

Prediction Plots

Validation Plots

Set or return options for the pls package

MSEP, RMSEP and R2 of PLSR and PCR models

Extract Information From a Fitted PLSR or PCR Model

Generate segments for cross-validation

Plot Regression Coefficients of PLSR and PCR models

Plots of Scores, Loadings and Correlation Loadings

CPPLS (Indahl et al.)

widekernelpls.fit

Wide Kernel PLS (R�nnar et al.)

Plot Method for MVR objects

Sensory and physico-chemical data of olive oils

Sijmen de Jong's SIMPLS

Extract Scores and Loadings from PLSR and PCR Models

Jackknife Variance Estimates of Regression Coefficients

Adjust for Missing Values

Predict Method for PLSR and PCR

Principal Component Regression