Classical least squares multivariate spectral analysis

Haaland, David M

Classical least squares multivariate spectral analysis

Patent · Mon Dec 31 23:00:00 EST 2001

OSTI ID:874560

Haaland, David M ^[1]

Albuquerque, NM

An improved classical least squares multivariate spectral analysis method that adds spectral shapes describing non-calibrated 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 CLS-type 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.

View Patent

Research Organization:: SANDIA CORP

DOE Contract Number:: AC04-94AL85000

Assignee:: Sandia Corporation (Albuquerque, NM)

Patent Number(s):: US 6415233

OSTI ID:: 874560

Country of Publication:: United States

Language:: English

References (15)

Methods to Include Beer's Law Nonlinearities in Quantitative Spectral Analysis Haaland, D. M.; McClure, G. L. Computerized Quantitative Infrared Analysis, p. 78-94 https://doi.org/10.1520/STP23164S	book	January 1987
Application of New Least-Squares Methods for the Quantitative Infrared Analysis of Multicomponent Samples Haaland, David M.; Easterling, Robert G. Applied Spectroscopy, Vol. 36, Issue 6 https://doi.org/10.1366/0003702824639114	journal	November 1982
New Prediction-Augmented Classical Least-Squares (PACLS) Methods: Application to Unmodeled Interferents Haaland, David M.; Melgaard, David K. Applied Spectroscopy, Vol. 54, Issue 9 https://doi.org/10.1366/0003702001951228	journal	September 2000
Error propagation and figures of merit for quantification by solving matrix equations Lorber, Avraham. Analytical Chemistry, Vol. 58, Issue 6 https://doi.org/10.1021/ac00297a042	journal	May 1986
Partial least-squares methods for spectral analyses. 1. Relation to other quantitative calibration methods and the extraction of qualitative information Haaland, David M.; Thomas, Edward V. Analytical Chemistry, Vol. 60, Issue 11 https://doi.org/10.1021/ac00162a020	journal	June 1988
Partial least-squares methods for spectral analyses. 2. Application to simulated and glass spectral data Haaland, David M.; Thomas, Edward V. Analytical Chemistry, Vol. 60, Issue 11 https://doi.org/10.1021/ac00162a021	journal	June 1988
Quantitative infrared analysis of borophosphosilicate films using multivariate statistical methods Haaland, David M. Analytical Chemistry, Vol. 60, Issue 11 https://doi.org/10.1021/ac00162a022	journal	June 1988
Comparison of multivariate calibration methods for quantitative spectral analysis Thomas, Edward V.; Haaland, David M. Analytical Chemistry, Vol. 62, Issue 10 https://doi.org/10.1021/ac00209a024	journal	May 1990
Improved Sensitivity of Infrared Spectroscopy by the Application of Least Squares Methods Haaland, David M.; Easterling, Robert G. Applied Spectroscopy, Vol. 34, Issue 5 https://doi.org/10.1366/0003702804731258	journal	September 1980
Spectral data files for self-modeling curve resolution with examples using the Simplisma approach Windig, W. Chemometrics and Intelligent Laboratory Systems, Vol. 36, Issue 1 https://doi.org/10.1016/S0169-7439(96)00061-5	journal	February 1997
Selectivity, local rank, three-way data analysis and ambiguity in multivariate curve resolution Tauler, Romà; Smilde, Age; Kowalski, Bruce Journal of Chemometrics, Vol. 9, Issue 1 https://doi.org/10.1002/cem.1180090105	journal	January 1995
Enhancing IR Detection Limits for Trace Polar Organics in Aqueous Solutions with Surface-Modified Sol-Gel-Coated ATR Sensors Han, Ling; Niemczyk, Thomas M.; Haaland, David M. Applied Spectroscopy, Vol. 53, Issue 4 https://doi.org/10.1366/0003702991946839	journal	April 1999
Multivariate Calibration Methods Applied to Quantitative FT-IR Analyses Haaland, David M. Practical Fourier Transform Infrared Spectroscopy, p. 395-468 https://doi.org/10.1016/B978-0-12-254125-4.50013-6	book	January 1990
Partial least-squares method for spectrofluorimetric analysis of mixtures of humic acid and lignin sulfonate Lindberg, Walter.; Persson, Jan-Aake.; Wold, Svante. Analytical Chemistry, Vol. 55, Issue 4 https://doi.org/10.1021/ac00255a014	journal	April 1983
Multivariate Least-Squares Methods Applied to the Quantitative Spectral Analysis of Multicomponent Samples Haaland, David M.; Easterling, Robert G.; Vopicka, David A. Applied Spectroscopy, Vol. 39, Issue 1 https://doi.org/10.1366/0003702854249376	journal	January 1985

Similar Records

Augmented Classical Least Squares Multivariate Spectral Analysis

Patent · Mon Jan 10 23:00:00 EST 2005 · OSTI ID:880185

Augmented Classical Least Squares Multivariate Spectral Analysis

Patent · Tue Jul 26 00:00:00 EDT 2005 · OSTI ID:880656

Augmented classical least squares multivariate spectral analysis

Patent · Mon Feb 02 23:00:00 EST 2004 · OSTI ID:1174715

Related Subjects

/702/430/
ability
accuracy
accurately
adds
analysis
analysis method
analyzed
application
applications
baseline
calibration
capabilities
classical
cls-type
components
concentrations
corrections
decrease
demonstrated
describing
drift
drifting
effects
eliminate
extend
finally
greatly
improved
improvements
incorporation
maintenance
method
methods
mixture
model
multivariate
non-calibrated
pacls
phase
precision
predict
prediction
quantitative
restrictions
sample
samples
shapes
spectral
spectrometer
spectrometers
squares
transfer
unmodeled

Classical least squares multivariate spectral analysis

Citation Formats

References (15)

Similar Records

Related Subjects