alkahest: Pre-Processing XY Data from Experimental Methods

A lightweight, dependency-free toolbox for pre-processing XY data from experimental methods (i.e. any signal that can be measured along a continuous variable). This package provides methods for baseline estimation and correction, smoothing, normalization, integration and peaks detection. Baseline correction methods includes polynomial fitting as described in Lieber and Mahadevan-Jansen (2003) <doi:10.1366/000370203322554518>, Rolling Ball algorithm after Kneen and Annegarn (1996) <doi:10.1016/0168-583X(95)00908-6>, SNIP algorithm after Ryan et al. (1988) <doi:10.1016/0168-583X(88)90063-8>, 4S Peak Filling after Liland (2015) <doi:10.1016/j.mex.2015.02.009> and more.

Version:	1.2.0
Depends:	R (≥ 3.5.0)
Imports:	grDevices, methods, stats, utils
Suggests:	knitr, Matrix, markdown, tinytest
Published:	2024-07-26
DOI:	10.32614/CRAN.package.alkahest
Author:	Nicolas Frerebeau [aut, cre] (Université Bordeaux Montaigne), Brice Lebrun [ctb] (Logo designer), Université Bordeaux Montaigne [fnd], CNRS [fnd]
Maintainer:	Nicolas Frerebeau <nicolas.frerebeau at u-bordeaux-montaigne.fr>
BugReports:	https://github.com/tesselle/alkahest/issues
License:	GPL (≥ 3)
URL:	https://packages.tesselle.org/alkahest/, https://github.com/tesselle/alkahest
NeedsCompilation:	no
Citation:	alkahest citation info
Materials:	README NEWS
CRAN checks:	alkahest results

Documentation:

Reference manual:	alkahest.pdf
Vignettes:	Baseline Smoothing Methods

Downloads:

Package source:	alkahest_1.2.0.tar.gz
Windows binaries:	r-devel: alkahest_1.2.0.zip, r-release: alkahest_1.2.0.zip, r-oldrel: alkahest_1.2.0.zip
macOS binaries:	r-release (arm64): alkahest_1.2.0.tgz, r-oldrel (arm64): alkahest_1.2.0.tgz, r-release (x86_64): alkahest_1.2.0.tgz, r-oldrel (x86_64): alkahest_1.2.0.tgz
Old sources:	alkahest archive

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