NOTICE: Due to a lapse in annual appropriations, most of this website is not being updated. Learn more.

Form submissions will still be accepted but will not receive responses at this time. Sections of this site for programs using non-appropriated funds (such as NVLAP) or those that are excepted from the shutdown (such as CHIPS and NVD) will continue to be updated.

U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

PUBLICATIONS

Stochastic Regression Modeling of Chemical Spectra

Published

Author(s)

Anthony J. Kearsley, William E. Wallace, Yutheeka Gadhyan

Abstract

A stochastic regression method has been developed that decomposes chemical spectra into separate contributions from signal and from noise. The numerical results of regressing in this way on sample spectra are presented. The results suggest that this strategy offers an effective and efficient framework for in-depth noise estimation and analysis. From this analysis more effective means of feature extraction in chemical spectra can be created.
Citation
Chemometrics and Intelligent Laboratory Systems
Pub Type
Journals

Download Paper

https://doi.org/10.1016/j.chemolab.2014.08.002

Keywords

Signal to noise, stochastic differential equation, nonparametric, estimation, mass spectrometry, spectroscopy
Modeling and simulation research, Metrology and Conformity assessment

Citation

Kearsley, A. , Wallace, W. and Gadhyan, Y. (2014), Stochastic Regression Modeling of Chemical Spectra, Chemometrics and Intelligent Laboratory Systems, [online], https://doi.org/10.1016/j.chemolab.2014.08.002 (Accessed October 28, 2025)

Issues

If you have any questions about this publication or are having problems accessing it, please contact [email protected].

Created August 14, 2014, Updated November 10, 2018
Was this page helpful?