Classical least squares multivariate spectral analysis
Abstract
An improved classical least squares multivariate spectral analysis method that adds spectral shapes describing noncalibrated components and system effects (other than baseline corrections) present in the analyzed mixture to the prediction phase of the method. These improvements decrease or eliminate many of the restrictions to the CLStype methods and greatly extend their capabilities, accuracy, and precision. One new application of PACLS includes the ability to accurately predict unknown sample concentrations when new unmodeled spectral components are present in the unknown samples. Other applications of PACLS include the incorporation of spectrometer drift into the quantitative multivariate model and the maintenance of a calibration on a drifting spectrometer. Finally, the ability of PACLS to transfer a multivariate model between spectrometers is demonstrated.
 Inventors:

 Albuquerque, NM
 Issue Date:
 Research Org.:
 SANDIA CORP
 OSTI Identifier:
 874560
 Patent Number(s):
 6415233
 Assignee:
 Sandia Corporation (Albuquerque, NM)
 DOE Contract Number:
 AC0494AL85000
 Resource Type:
 Patent
 Country of Publication:
 United States
 Language:
 English
 Subject:
 classical; squares; multivariate; spectral; analysis; improved; method; adds; shapes; describing; noncalibrated; components; effects; baseline; corrections; analyzed; mixture; prediction; phase; improvements; decrease; eliminate; restrictions; clstype; methods; greatly; extend; capabilities; accuracy; precision; application; pacls; ability; accurately; predict; sample; concentrations; unmodeled; samples; applications; incorporation; spectrometer; drift; quantitative; model; maintenance; calibration; drifting; finally; transfer; spectrometers; demonstrated; analysis method; /702/430/
Citation Formats
Haaland, David M. Classical least squares multivariate spectral analysis. United States: N. p., 2002.
Web.
Haaland, David M. Classical least squares multivariate spectral analysis. United States.
Haaland, David M. Tue .
"Classical least squares multivariate spectral analysis". United States. https://www.osti.gov/servlets/purl/874560.
@article{osti_874560,
title = {Classical least squares multivariate spectral analysis},
author = {Haaland, David M},
abstractNote = {An improved classical least squares multivariate spectral analysis method that adds spectral shapes describing noncalibrated components and system effects (other than baseline corrections) present in the analyzed mixture to the prediction phase of the method. These improvements decrease or eliminate many of the restrictions to the CLStype methods and greatly extend their capabilities, accuracy, and precision. One new application of PACLS includes the ability to accurately predict unknown sample concentrations when new unmodeled spectral components are present in the unknown samples. Other applications of PACLS include the incorporation of spectrometer drift into the quantitative multivariate model and the maintenance of a calibration on a drifting spectrometer. Finally, the ability of PACLS to transfer a multivariate model between spectrometers is demonstrated.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2002},
month = {1}
}