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pls (version 2.4-3)

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

2.4-3

License

GPL-2

Maintainer

Bj�rn-Helge Mevik

Last Published

August 10th, 2013

Functions in pls (2.4-3)

Sensory and physico-chemical data of olive oils

Jackknife Variance Estimates of Regression Coefficients

widekernelpls.fit

Wide Kernel PLS (R�nnar et al.)

Plot Method for MVR objects

Biplots of PLSR and PCR Models.

Cross-validation of PLSR and PCR models

Generate segments for cross-validation

Principal Component Regression

Adjust for Missing Values

Kernel PLS (Dayal and MacGregor)

Cross-validation

Partial Least Squares and Principal Component Regression

Prediction Plots

MSEP, RMSEP and R2 of PLSR and PCR models

Standardization of Data Matrices

Plots of Scores, Loadings and Correlation Loadings

NIR measurements and oil types of mayonnaise

Sijmen de Jong's SIMPLS

Orthogonal scores PLSR

Set or return options for the pls package

Jackknife approximate t tests of regression coefficients

Octane numbers and NIR spectra of gasoline

Extract Information From a Fitted PLSR or PCR Model

Summary and Print Methods for PLSR and PCR objects

Predict Method for PLSR and PCR

Validation Plots

CPPLS (Indahl et al.)

Plot Regression Coefficients of PLSR and PCR models

Extract Scores and Loadings from PLSR and PCR Models

delete.intercept

Delete intercept from model matrix

Multiplicative Scatter Correction

NIR spectra and density measurements of PET yarns