Chemometrics and computational physics are concerned with the analysis
of data arising in chemistry and physics experiments, as well as the
simulation of physicochemico systems. Many of the functions in base
R are useful for these ends.
The book
Chemometrics with R
by Ron Wehrens,
ISBN: 9783642178405, 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 package
ChemometricsWithR.
The book
Modern Statistical Methods for Astronomy With R Applications
by Eric D. Feigelson and G. Jogesh Babu, ISBN13: 9780521767279, Cambridge, 2012,
provides an introduction to statistics for astronomers and an
overview of the foremost methods being used in astrostatistical analysis,
illustrated by examples in R.
The book by Kurt Varmuza and Peter Filzmoser,
Introduction to Multivariate Statistical Analysis in Chemometrics,
ISBN 9781420059472, 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
oscopy 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 nonnegative or nonpositive 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 by
nlreg.
Curve Resolution

The
PTAk
package provides functions for
Principal Tensor Analysis on k modes.
The package includes also some other multiway methods:
PCAn (Tuckern) and PARAFAC/CANDECOMP.

Multivariate curve resolution alternating least squares (MCRALS)
is implemented in the package
ALS.

The
alsace
package provides MCRALS support for Liquid chromatography with PhotoDiode Array Detection
(LCDAD) data with
many injections, with features for peak alignment and identification.

The package
drc
provides functions for the analysis
of one or multiple nonlinear curves with focus on models for
concentrationresponse, doseresponse and timeresponse data.
Partial Least Squares

The package
pls
implements
Partial Least Squares Regression (PLSR) and Principal
Component Regression (PCR).

The package
lspls
implements the
least squarespartial least squares (LSPLS) 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.

Package
plspm
contains, in addition to the
usual functions for PLS regression, also functions for
path modeling.

The package
enpls
implements ensemble partial
least squares, a
framework for measuring feature importance, outlier detection,
and ensemble modeling based on (sparse) partial least squares
regressions.
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 Gififamily).

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.
Compositional Data Analysis

The package
compositions
provides functions for the consistent analysis of compositional data (e.g. portions of substances) and positive numbers (e.g. concentrations).
See also the book,
Analyzing Compositional Data with
R
by K. Gerald von den Boogaart und Raimon TolosanaDelgado,
ISBN: 9783642368080, Springer, 2013.
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
leapsandbounds 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
leapsandbounds algorithms, as well as local refinements.

Package
varSelRF
provides variable selection methods for random
forests. Crossvalidationbased variable selection using Wilcoxon rank
sum tests is available in package
WilcoxCV, focused on
binary classification in microarrays. Package
clustvarsel
implements variable selection for modelbased clustering.

The
BioMark
package
implements two metamethods for variable selection: stability selection (applying a primary selection method like a ttest, VIP value or PLSDA regression coefficient) to different subsets of the data, and higher criticism, which provides a datadriven choice of significance cutoffs in statistical testing.
SelfOrganizing Maps

The
kohonen
package implements selforganizing maps as well as
some extensions for supervised pattern recognition and data fusion.
The
som
package provides functions for selforganizing maps.
Differential Equations
Calibration

The
investr
package facilitates calibration/inverse
estimation with linear and nonlinear regression models.

The
chemCal
package provides functions for plotting
linear calibration functions and estimating standard errors for
measurements.

The
nlreg
package is useful for nonlinear calibration models.

The package
represent
calculates the 'representativity'
of two multidimensional
datasets, which involves comparison of the similarity of principal component
analysis loading patterns, variancecovariance matrix structures,
and data set centroid locations.
Cellular Automata

The
simecol
package includes functions for cellular automata
modeling.
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).

ChemmineR
is
a cheminformatics toolkit for analyzing small molecules in R. Its addon
packages include
fmcsR
for
mismatch tolerant maximum common substructure matching,
eiR
for
accelerated structure similarity searching;
bioassayR
for analyzing bioactivity data, and
ChemmineOB
for accessing
OpenBabel
functionalities from R.

The
webchem
package allows users to retrieve chemical information
from various sources on the web and to interact with various APIs. Sources
include:
Chemical Identifier Resolver
,
ChemSpider
,
PubChem
,
Chemical Translation Service
,
PAN Pesticide Database
,
Alan Wood's Compendium of Pesticide Common Names
,
PHYSPROP Database
,
ETOX
,
PPDB
, and
ChemIDplus
.
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 userfriendly
functions for plotting spectra (NMR, IR, etc) and
carrying topdown exploratory data analysis, such as HCA, PCA
and modelbased clustering.

The
HyperChemoBridge
interconverts
ChemoSpec
and
hyperSpec
objects

The
Peaks
package implements functions for spectrum
manipulation, ported from the ROOT/TSpectrum class.

The
speaq
package implements the hierarchical Clusterbased Peak Alignment (CluPA) and may be used for aligning NMR spectra.

Software for the book by Donald B. Percival and Andrew T. Walden,
Spectral Analysis for Physical Applications,
ISBN 9780521435413,
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 timeresolved spectroscopy data.

The package
prospectr
provides functions for pretreatment and sample selection of visible and near infrared diffuse reflectance spectra.

The
resemble
includes functions for spectral dissimilarity analysis and memorybased learning (a.k.a. local modeling) for nonlinear modeling in spectral datasets.
Mass Spectrometry

The
MSnbase
defines infrastructure for
mass spectrometrybased proteomics data handling,
plotting, processing and quantification.

The
MALDIquant
provides tools for quantitative analysis
of MALDITOF 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 TransformIon Cyclotron
Resonance Mass Spectrometry Data.

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.

The
apLCMS
package is designed for the processing of LC/MS based metabolomics data.

The
xMSanalyzer
package allows merging
apLCMS
sample processing results from multiple sets of parameter
settings, among other features.

The
MSPrep
package is for postprocessing of metabolomic data, including summarization of replicates, filtering, imputation, and normalization.

The
metaMS
package is an MSbased metabolomics data processing and compound annotation pipeline.
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.
Fluorescence ExcitationEmission Matrix (EEM)

The
EEM
reads raw EEM
data and prepares it for further analysis.
Carbon Dating

The package
Bchron
creates
chronologies based on radiocarbon and nonradiocarbon dated depths.
XRay Diffractograms

The
diffractometry
package provides
baseline identification and peak decomposition for xray
diffractograms.
Astronomy and astrophysics

The
astrodatR
package collects 19 datasets from
contemporary astronomy research, many of which are described in the aforementioned textbook â€˜Modern Statistical Methods for Astronomy with R Applicationsâ€™.

The
astrolibR
package presents an R interface to lowlevel utilities and codes from the
Interactive Data Language (IDL) Astronomy Users Library
.

The
CosmoPhotoz
package performs
photometric redshift estimation using generalized linear models.

The
CRAC
collects R functions for cosmological research, with
its main functions being similar to the python library, cosmolopy.

The
RobPer
package calculates periodograms based on (robustly) fitting periodic functions to light curves.

The package
snapshot
contains functions for reading and writing Nbody snapshots from the GADGET code for cosmological Nbody/SPH simulations.

The package
UPMASK
performs unsupervised photometric membership assignment in stellar clusters using, e.g., photometry and spatial
positions.

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.

The
FITSio
package provides utilities to read and write files in the FITS (Flexible Image Transport System) format, a standard format in astronomy.

The
stellaR
package manages and displays stellar tracks and isochrones from the Pisa lowmass database.

The
astroFns
provides miscellaneous astronomy functions, utilities, and data.

The
cosmoFns
contains standard expressions for
distances, times, luminosities, and other quantities useful in
observational cosmology, including molecular line observations.

The
astro
package provides tools for astronomy; functions
provided may be grouped into 4 main areas: cosmology, FITS file manipulation, the Sersic function and general (plotting and scripting) tools.

The
celestial
package includes a number of common astronomy conversion routines, particularly the HMS and degrees schemes.

The
SCEPtER
package
is used to
estimate stellar mass and radius given observational data of effective
temperature, [Fe/H], and astroseismic parameters.

The
lira
package performs Bayesian linear regression and forecasting in Astronomy, accounting for all kinds of errors and correlations in the data.

The
astrochron
package contains routines for astronomical time scale construction, time series analysis, time scale development, and paleoclimate analysis.

The
SPADAR
package provides functions to create allsky grid plots of widely used astronomical coordinate systems (equatorial, ecliptic, galactic) and scatter plots of data on any of these systems, including onthefly system conversion.

The
SCEPtERbinary
allows for estimating the stellar age for doublelined detached binary systems, adopted from the effective temperature, the metallicity [Fe/H], the mass, and the radius of the two stars.

The
Astrostatistics and Astroinformatics Portal
is an Rcentric collection of information regarding statistical analysis in astronomy.

Hans Werner Borchers has a page on
Astronomy modules and links for R, Python, and Julia
.
Optics and Scattering Approximations

The
planar
package provides code to simulate
reflection and transmission at a multilayer planar interface.

The
dielectric
package defines some physical constants and dielectric functions commonly used in optics and plasmonics.
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 airwater
exchange.

See the
Environmetrics
task view for further related
packages related to water and soil chemistry.
Titration Curves

The
titrationCurves
package provides functions to plot
acid/base, complexation, redox, and precipitation titration curves.