r-pls 2.7-3 Partial Least Squares and Principal Component Regression
The pls package implements multivariate regression methods: Partial Least Squares Regression (PLSR), Principal Component Regression (PCR), and Canonical Powered Partial Least Squares (CPPLS). It supports:
several algorithms: the traditional orthogonal scores (NIPALS) PLS algorithm, kernel PLS, wide kernel PLS, Simpls, and PCR through
svd
multi-response models (or PLS2)
flexible cross-validation
Jackknife variance estimates of regression coefficients
extensive and flexible plots: scores, loadings, predictions, coefficients, (R)MSEP, R², and correlation loadings
formula interface, modelled after
lm()
, with methods for predict, print, summary, plot, update, etc.extraction functions for coefficients, scores, and loadings
MSEP, RMSEP, and R² estimates
multiplicative scatter correction (MSC)
- Website: https://mevik.net/work/software/pls.html
- License: GPL 2
- Package source: cran.scm
- Patches: None
- Builds: x86_64-linux, i686-linux