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.
- Version1.2.0
- R versionunknown
- LicenseGPL (≥ 3)
- Needs compilation?No
- alkahest citation info
- Last release07/26/2024
Documentation
Team
Nicolas Frerebeau
MaintainerShow author detailsBrice Lebrun
Université Bordeaux Montaigne
Show author detailsRolesfndCNRS
Show author detailsRolesfnd
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