Hybrid least squares multivariate spectral analysis methods
Abstract
A set of hybrid least squares multivariate spectral analysis methods in which spectral shapes of components or effects not present in the original calibration step are added in a following estimation or calibration step to improve the accuracy of the estimation of the amount of the original components in the sampled mixture. The "hybrid" method herein means a combination of an initial classical least squares analysis calibration step with subsequent analysis by an inverse multivariate analysis method. A "spectral shape" herein means normally the spectral shape of a noncalibrated chemical component in the sample mixture but can also mean the spectral shapes of other sources of spectral variation, including temperature drift, shifts between spectrometers, spectrometer drift, etc. The "shape" can be continuous, discontinuous, or even discrete points illustrative of the particular effect.
 Inventors:

 Albuquerque, NM
 Issue Date:
 Research Org.:
 SANDIA CORP
 OSTI Identifier:
 874212
 Patent Number(s):
 6341257
 Assignee:
 Sandia Corporation (Albuquerque, NM)
 DOE Contract Number:
 AC0494AL85000
 Resource Type:
 Patent
 Country of Publication:
 United States
 Language:
 English
 Subject:
 hybrid; squares; multivariate; spectral; analysis; methods; set; shapes; components; effects; original; calibration; step; added; following; estimation; improve; accuracy; amount; sampled; mixture; method; means; combination; initial; classical; subsequent; inverse; shape; normally; noncalibrated; chemical; component; sample; mean; sources; variation; including; temperature; drift; shifts; spectrometers; spectrometer; etc; continuous; discontinuous; discrete; illustrative; effect; analysis method; /702/703/
Citation Formats
Haaland, David M. Hybrid least squares multivariate spectral analysis methods. United States: N. p., 2002.
Web.
Haaland, David M. Hybrid least squares multivariate spectral analysis methods. United States.
Haaland, David M. Tue .
"Hybrid least squares multivariate spectral analysis methods". United States. https://www.osti.gov/servlets/purl/874212.
@article{osti_874212,
title = {Hybrid least squares multivariate spectral analysis methods},
author = {Haaland, David M},
abstractNote = {A set of hybrid least squares multivariate spectral analysis methods in which spectral shapes of components or effects not present in the original calibration step are added in a following estimation or calibration step to improve the accuracy of the estimation of the amount of the original components in the sampled mixture. The "hybrid" method herein means a combination of an initial classical least squares analysis calibration step with subsequent analysis by an inverse multivariate analysis method. A "spectral shape" herein means normally the spectral shape of a noncalibrated chemical component in the sample mixture but can also mean the spectral shapes of other sources of spectral variation, including temperature drift, shifts between spectrometers, spectrometer drift, etc. The "shape" can be continuous, discontinuous, or even discrete points illustrative of the particular effect.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2002},
month = {1}
}