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alkahest  

Pre-Processing XY Data from Experimental Methods
View on CRAN: Click here


Download and install alkahest package within the R console
Install from CRAN:
install.packages("alkahest")

Install from Github:
library("remotes")
install_github("cran/alkahest")

Install by package version:
library("remotes")
install_version("alkahest", "1.2.0")



Attach the package and use:
library("alkahest")
Maintained by
Nicolas Frerebeau
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-09-15
Latest Update: 2023-06-13
Description:
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) , Rolling Ball algorithm after Kneen and Annegarn (1996) , SNIP algorithm after Ryan et al. (1988) , 4S Peak Filling after Liland (2015) and more.
How to cite:
Nicolas Frerebeau (2022). alkahest: Pre-Processing XY Data from Experimental Methods. R package version 1.2.0, https://cran.r-project.org/web/packages/alkahest. Accessed 21 Nov. 2024.
Previous versions and publish date:
1.0.0 (2022-09-15 12:00), 1.1.0 (2023-05-18 11:10), 1.1.1 (2023-06-13 09:50)
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