Chemometrics and computational physics are concerned with the analysis of data arising in chemistry and physics experiments, as well as the simulation of physico-chemico systems. Many of the functions in base R are useful for these ends.

The book Chemometrics with R , by Ron Wehrens, ISBN: 978-3-642-17840-5, Springer, 2011, provides an introduction to multivariate statistics in the life sciences, as well as coverage of several specific topics from the area of chemometrics; the examples in the book are possible to reproduce using the packages ChemometricsWithR and ChemometricsWithRData.

The book by Kurt Varmuza and Peter Filzmoser, Introduction to Multivariate Statistical Analysis in Chemometrics , ISBN 978-1-420-05947-2, CRC Press, 2009, is associated with the package chemometrics.

A special issue of R News with a focus on R in Chemistry was published in August 2006. A special volume of Journal of Statistical Software (JSS) dedicated to Spectroscopy and Chemometrics in R was published in January 2007.

Please let us know if we have omitted something of importance, or if a new package or function should be mentioned here.

Linear Regression Models

• Linear models can be fitted (via OLS) with lm() (from stats). A least squares solution for x in Ax = b can also be computed as qr.coef(qr(A), b).
• The package nnls provides a means of constraining x to non-negative or non-positive values; the package bvls allows other bounds on x to be applied.
• Functions for isotonic regression are available in the package Iso, and are useful to determine the unimodal vector that is closest to a given vector x under least squares criteria.
• Heteroskedastic linear models can be fit using the gls() function of the nlme package.

Nonlinear Regression Models

• The nls() function (from stats) as well as the package minpack.lm allow the solution of nonlinear least squares problems.
• Correlated and/or unequal variances can be modeled using the gnls() function of the nlme package and the nlreg.

Curve Resolution

• The PTAk package provides functions for Principal Tensor Analysis on k modes. The package includes also some other multiway methods: PCAn (Tucker-n) and PARAFAC/CANDECOMP.
• Multivariate curve resolution alternating least squares (MCR-ALS) is implemented in the package ALS.
• The package drc provides functions for the analysis of one or multiple non-linear curves with focus on models for concentration-response, dose-response and time-response data.

Partial Least Squares

• The package pls implements Partial Least Squares Regression (PLSR) and Principal Component Regression (PCR).
• The package plsRglm implements partial least squares regression for generalized linear models and k-fold cross-validation of such models, with options for Bootstrap confidence intervals and significance testing.
• The package lspls implements the least squares-partial least squares (LS-PLS) method.
• Penalized Partial Least Squares is implemented in the ppls package.
• Sparse PLS is implemented in the package spls package.
• The gpls package implements generalized partial least squares, based on the Iteratively ReWeighted Least Squares (IRWLS) method of Brian Marx.
• Weighted-average PLS, often used in paleolimnology, can be found in package paltran.
• Package plspm contains, in addition to the usual functions for PLS regression, also functions for path modeling.

Principal Component Analysis

• Principal component analysis (PCA) is in the package stats as functions princomp(). Some graphical PCA representations can be found in the psy package.
• The homals package provides nonlinear PCA and, by defining sets, nonlinear canonical correlation analysis (models of the Gifi-family).
• A desired number of robust principal components can be computed with the pcaPP package. The package elasticnet is applicable to sparse PCA. The package fpca can be applied to restricted MLE for functional PCA.
• See the Multivariate task view for further packages dealing with PCA and other projection methods.

Factor Analysis

• Factor analysis (FA) is in the package stats as functions factanal(); see Psychometrics task view for details on extensions.

Independent Component Analysis

• Independent component analysis (ICA) can be computed using fastICA.

Clustering

• The Cluster task view provides a list of packages that can be used for clustering problems.

Variable Selection

• Stepwise variable selection for linear models, using AIC, is available in function step(); package leaps implements leaps-and-bounds variable selection, by default using Mallow's Cp. stepPlr provides stepwise variable selection for penalized logistic regression.
• Variable selection based on evolutionary algorithms is available in package and subselect. The latter also provides simulated annealing and leaps-and-bounds algorithms, as well as local refinements.
• Package varSelRF provides variable selection methods for random forests. Cross-validation-based variable selection using Wilcoxon rank sum tests is available in package WilcoxCV, focused on binary classification in microarrays. Package clustvarsel implements variable selection for model-based clustering.

Self-Organizing Maps

• The kohonen package implements self-organizing maps as well as some extensions for supervised pattern recognition and data fusion. The som package provides functions for self-organizing maps.
• The package wccsom provides SOM networks for comparing patterns with peak shifts.

Differential Equations

• The package deSolve provides general solvers for initial value problems of ordinary differential equations (ODE), partial differential equations (PDE), differential algebraic equations (DAE), and delay differential equations (DDE).
• The package ddesolve provides a solver for Delay Differential Equations.
• The package sde is the companion to the book by Stefano M. Iacus, Simulation and Inference for Stochastic Differential Equations, With R Examples , ISBN 978-0-387-75838-1, Springer-Verlag, 2008.
• The simecol package provides functions to implement (ecological) models based on differential equations.

Calibration

• The chemCal package provides functions for plotting linear calibration functions and estimating standard errors for measurements.
• The quantchem package provides functions for statistical evaluation of calibration curves by different regression techniques
• The drm package and the nlreg package are useful for nonlinear calibration models.

Cellular Automata

• The simecol package includes functions for cellular automata modeling. One-dimensional cellular automata are also possible to model with the package CellularAutomaton.

Thermodynamics

• The CHNOSZ package provides functions for calculating the standard Gibbs energies and other thermodynamic properties, and chemical affinities of reactions between species contained in a thermodynamic database.

Interfaces to External Libraries

• The package rcdk allows the user to access functionality in the Chemistry Development Kit (CDK) , a Java framework for cheminformatics. This allows the user to load molecules, evaluate fingerprints, calculate molecular descriptors and so on. In addition, the CDK API allows the user to view structures in 2D. The rcdklibs package provides the CDK libraries for use in R.
• The rpubchem package gives access to PubChem data (compounds, substance, assays).
• The ChemmineR package provides an interface to the ChemMine database for structural structural similarity searching and clustering.

Spectroscopy

• The hyperSpec packages allows analysis of hyperspectral data, i.e., spectra plus further information such as spatial information, time, concentrations, etc. Such data are frequently encountered in the analysis of Raman, IR, NIR, UV/VIS, NMR, etc., spectroscopic data sets.
• The ChemoSpec package collects user-friendly functions for plotting spectra (NMR, IR, etc) and carrying top-down exploratory data analysis, such as HCA, PCA and model-based clustering.
• The Peaks package implements functions for spectrum manipulation, ported from the ROOT/TSpectrum class.
• Software for the book by Donald B. Percival and Andrew T. Walden, Spectral Analysis for Physical Applications , ISBN 978-0-521-43541-3, Cambridge University Press, 1993, is found in the package sapa.
• The package TIMP provides a problem solving environment for fitting separable nonlinear models in physics and chemistry applications, and has been extensively applied to time-resolved spectroscopy data.
• The package NMRS is designed to load and preprocess nuclear magnetic resonance spectra measured with Bruker instruments.
• Also note that the photonics project on R-Forge collects various packages related to spectroscopy and optics; however, these packages are not yet available on CRAN.

Mass Spectrometry

• The MSnbase defines infrastructure for mass spectrometry-based proteomics data handling, plotting, processing and quantification.
• The MALDIquant provides tools for quantitative analysis of MALDI-TOF mass spectrometry data, with support for baseline correction, peak detection and plotting of mass spectra.
• The OrgMassSpecR package is for organic/biological mass spectrometry, with a focus on graphical display, quantification using stable isotope dilution, and protein hydrogen/deuterium exchange experiments.
• The FTICRMS package provides functions for Analyzing Fourier Transform-Ion Cyclotron Resonance Mass Spectrometry Data.
• Processing and classification of SELDI data is available in caMassClass.
• The msProcess package provides functions for protein mass spectra processing. Data sets associated with msProcess can be found in three separate packages: msBreast, msDilution and msProstate.
• The titan provides a GUI to analyze mass spectrometric data on the relative abundance of two substances from a titration series.
• The Bioconductor packages MassSpecWavelet, PROcess, and xcms are designed for the analysis of mass spectrometry data.

Functional Magnetic Resonance Imaging

• Functions for I/O, visualization and analysis of functional Magnetic Resonance Imaging (fMRI) datasets stored in the ANALYZE or NIFTI format are available in the package AnalyzeFMRI. The package fmri contains functions to analyze fMRI data using adaptive smoothing procedures.

Fluorescence Lifetime Imaging Microscopy

• Functions for visualization and analysis of Fluorescence Lifetime Imaging Microscopy (FLIM) datasets are available in the package TIMP.

Carbon Dating

• The package Bchron creates chronologies based on radiocarbon and non-radiocarbon dated depths.

X-Ray Diffractograms

• The diffractometry package provides baseline identification and peak decomposition for x-ray diffractograms. Cross-correlation based comparison of diffractograms is provided in package wccsom.

Astronomy

• The moonsun package provides functions for basic astronomical calculations.
• The solaR package provides functions to determine the movement of the sun from the earth and to determine incident solar radiation.

Energy Modeling

• The solaR package provides functions to simulate and model systems involved in the capture and use of solar energy, including photovoltaics.

Positron Emission Tomography

• The PET package implements different analytic/direct and iterative reconstruction methods for positron emission tomography (PET) data.

Water and Soil Chemistry

• The AquaEnv package is a toolbox for aquatic chemical modelling focused on (ocean) acidification and CO2 air-water exchange.
• See the Environmetrics task view for further related packages related to water and soil chemistry.