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pls (version 2.5-0)

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

2.5-0

License

GPL-2

Maintainer

Bj�rn-Helge Mevik

Last Published

August 22nd, 2015

Functions in pls (2.5-0)

Jackknife approximate t tests of regression coefficients

CPPLS (Indahl et al.)

Octane numbers and NIR spectra of gasoline

Cross-validation of PLSR and PCR models

Prediction Plots

Predict Method for PLSR and PCR

Partial Least Squares and Principal Component Regression

MSEP, RMSEP and R2 of PLSR and PCR models

Multiplicative Scatter Correction

Extract Scores and Loadings from PLSR and PCR Models

Jackknife Variance Estimates of Regression Coefficients

Sijmen de Jong's SIMPLS

Extract Information From a Fitted PLSR or PCR Model

Generate segments for cross-validation

Kernel PLS (Dayal and MacGregor)

Biplots of PLSR and PCR Models.

Summary and Print Methods for PLSR and PCR objects

Orthogonal scores PLSR

widekernelpls.fit

Wide Kernel PLS (Rännar et al.)

Standardization of Data Matrices

NIR measurements and oil types of mayonnaise

Validation Plots

Sensory and physico-chemical data of olive oils

Cross-validation

Plot Method for MVR objects

Adjust for Missing Values

delete.intercept

Delete intercept from model matrix

Set or return options for the pls package

Plot Regression Coefficients of PLSR and PCR models

Principal Component Regression

Plots of Scores, Loadings and Correlation Loadings

NIR spectra and density measurements of PET yarns