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chemometrics (version 1.3.9)

Multivariate Statistical Analysis in Chemometrics

Description

This package is the R companion to the book "Introduction to Multivariate Statistical Analysis in Chemometrics" written by K. Varmuza and P. Filzmoser (2009)

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Install

install.packages('chemometrics')

Monthly Downloads

6,354

Version

1.3.9

License

GPL (>= 3)

Maintainer

P. Filzmoser

Last Published

January 16th, 2015

Functions in chemometrics (1.3.9)

isometric logratio transformation

compute and plot cluster validity

Plot trimmed SEP from repeated DCV of PRM

Diagnostics plot for PCA

Eigenvector algorithm for PLS

Phenyl data set

Hyptis data set

Classification tree evaluation by CV

PCA diagnostics for variables

Stepwise regression

additive logratio transformation

Data from cereals

Plot results of Ridge regression

glass vessels data

Plot residuals from repeated DCV of PRM

Plot residuals from repeated DCV

Plot predictions from repeated DCV of PRM

Plot predictions from repeated DCV

chemometrics-package

This package is the R companion to the book "Introduction to Multivariate Statistical Analysis in Chemometrics" written by K. Varmuza and P. Filzmoser (2009).

Draws ellipses according to Mahalanobis distances

PCA calculation with the NIPALS algorithm

Neural network evaluation by CV

Repeated double-cross-validation for robust PLS

Repeated double-cross-validation for PLS and PCR

CV for Lasso regression

kNN evaluation by CV

Repeated Cross Validation for lm

Support Vector Machine evaluation by CV

Determine the number of PCA components with repeated cross validation

Generating random projection directions

Component plot for repeated DCV of PRM

Plot SEP from repeated DCV

Plot SOM results

Component plot for repeated DCV

Cross-validation for robust PLS

glass types of the glass data

GC retention indices

centered logratio transformation

Plot results from robust PLS

Delete intercept from model matrix

Plots classical and robust Mahalanobis distances

Plot Lasso coefficients

Repeated CV for Ridge regression

Trimmed standard deviation