Model for spectral and chromatographic data
Abstract
A method and apparatus using a spectral analysis technique are disclosed. In one form of the invention, probabilities are selected to characterize the presence (and in another form, also a quantification of a characteristic) of peaks in an indexed data set for samples that match a reference species, and other probabilities are selected for samples that do not match the reference species. An indexed data set is acquired for a sample, and a determination is made according to techniques exemplified herein as to whether the sample matches or does not match the reference species. When quantification of peak characteristics is undertaken, the model is appropriately expanded, and the analysis accounts for the characteristic model and data. Further techniques are provided to apply the methods and apparatuses to process control, cluster analysis, hypothesis testing, analysis of variance, and other procedures involving multiple comparisons of indexed data.
- Inventors:
-
- Richland, WA
- Issue Date:
- Research Org.:
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 874906
- Patent Number(s):
- 6487523
- Assignee:
- Battelle Memorial Institute (Richland, WA)
- Patent Classifications (CPCs):
-
G - PHYSICS G06 - COMPUTING G06K - RECOGNITION OF DATA
G - PHYSICS G01 - MEASURING G01N - INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- DOE Contract Number:
- AC06-76RL01830
- Resource Type:
- Patent
- Country of Publication:
- United States
- Language:
- English
- Subject:
- model; spectral; chromatographic; data; method; apparatus; analysis; technique; disclosed; form; probabilities; selected; characterize; presence; quantification; characteristic; peaks; indexed; set; samples; match; reference; species; acquired; sample; determination; techniques; exemplified; matches; peak; characteristics; undertaken; appropriately; expanded; accounts; provided; apply; methods; apparatuses; process; control; cluster; hypothesis; testing; variance; procedures; involving; multiple; comparisons; process control; analysis technique; /702/250/
Citation Formats
Jarman, Kristin, Willse, Alan, Wahl, Karen, and Wahl, Jon. Model for spectral and chromatographic data. United States: N. p., 2002.
Web.
Jarman, Kristin, Willse, Alan, Wahl, Karen, & Wahl, Jon. Model for spectral and chromatographic data. United States.
Jarman, Kristin, Willse, Alan, Wahl, Karen, and Wahl, Jon. Tue .
"Model for spectral and chromatographic data". United States. https://www.osti.gov/servlets/purl/874906.
@article{osti_874906,
title = {Model for spectral and chromatographic data},
author = {Jarman, Kristin and Willse, Alan and Wahl, Karen and Wahl, Jon},
abstractNote = {A method and apparatus using a spectral analysis technique are disclosed. In one form of the invention, probabilities are selected to characterize the presence (and in another form, also a quantification of a characteristic) of peaks in an indexed data set for samples that match a reference species, and other probabilities are selected for samples that do not match the reference species. An indexed data set is acquired for a sample, and a determination is made according to techniques exemplified herein as to whether the sample matches or does not match the reference species. When quantification of peak characteristics is undertaken, the model is appropriately expanded, and the analysis accounts for the characteristic model and data. Further techniques are provided to apply the methods and apparatuses to process control, cluster analysis, hypothesis testing, analysis of variance, and other procedures involving multiple comparisons of indexed data.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2002},
month = {11}
}
Works referenced in this record:
Multivariate statistical process control in chromatography
journal, August 1997
- Nijhuis, A.; de Jong, S.; Vandeginste, B. G. M.
- Chemometrics and Intelligent Laboratory Systems, Vol. 38, Issue 1