Multivariate Statistical Analysis in Chemometrics
additive logratio transformation
This package is the R companion to the book "Introduction to Multivari...
centered logratio transformation
compute and plot cluster validity
Delete intercept from model matrix
Draws ellipses according to Mahalanobis distances
isometric logratio transformation
kNN evaluation by CV
Plot Lasso coefficients
CV for Lasso regression
Repeated Cross Validation for lm
Plots classical and robust Mahalanobis distances
Repeated double-cross-validation for PLS and PCR
PCA calculation with the NIPALS algorithm
Neural network evaluation by CV
Determine the number of PCA components with repeated cross validation
Diagnostics plot for PCA
PCA diagnostics for variables
Component plot for repeated DCV
Component plot for repeated DCV of PRM
Plot predictions from repeated DCV
Plot predictions from repeated DCV of PRM
Plot results from robust PLS
Plot residuals from repeated DCV
Plot residuals from repeated DCV of PRM
Plot results of Ridge regression
Plot SEP from repeated DCV
Plot trimmed SEP from repeated DCV of PRM
Plot SOM results
Eigenvector algorithm for PLS
PLS1 by NIPALS
PLS2 by NIPALS
Robust PLS
Cross-validation for robust PLS
Repeated double-cross-validation for robust PLS
Repeated CV for Ridge regression
Generating random projection directions
Trimmed standard deviation
Stepwise regression
Support Vector Machine evaluation by CV
Classification tree evaluation by CV
R companion to the book "Introduction to Multivariate Statistical Analysis in Chemometrics" written by K. Varmuza and P. Filzmoser (2009).