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sabarsi  

Background Removal and Spectrum Identification for SERS Data
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("sabarsi", "0.1.0")



Attach the package and use:
library("sabarsi")
Maintained by
Li Jun
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-08-08
Latest Update: 2023-04-03
Description:
Implements a new approach SABARSI described in Wang et al. A Statistical Approach of Background Removal and Spectrum Identification for SERS Data Unpublished.Sabarsi forms a pipeline for SERS surface-enhanced Raman scattering data analysis including background removal signal detection signal integration and cross-experiment comparison. The background removal algorithm the very first step of SERS data analysis takes into account the change of background shape.
How to cite:
Li Jun (2019). sabarsi: Background Removal and Spectrum Identification for SERS Data. R package version 0.1.0, https://cran.r-project.org/web/packages/sabarsi
Previous versions and publish date:
0.1.0 (2019-08-08 14:30)
Other packages that cited sabarsi R package
View sabarsi citation profile
Other R packages that sabarsi depends, imports, suggests or enhances
Functions, R codes and Examples using the sabarsi R package
Some associated functions: SERS . background_removal . detect_sig . merge_signals . shift_match . signal_detection . 
Some associated R codes: SABARSI.R . SERS.dat.R . internal_functions.R .  Full sabarsi package functions and examples
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