Comparison of multivariate calibration methods for quantitative spectral analysis

Journal Article · Tue May 15 00:00:00 EDT 1990 · Analytical Chemistry (Washington); (USA)

DOI:https://doi.org/10.1021/ac00209a024· OSTI ID:6279672

Thomas, E V; Haaland, D M ^[1]

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1. Sandia National Laboratories, Albuquerque, NM (USA)

The quantitative prediction abilities of four multivariate calibration methods for spectral analyses are compared by using extensive Monte Carlo simulations. The calibration methods compared include inverse least-squares (ILS), classical least-squares (CLS), partial least-squares (PLS), and principal component regression (PCR) methods. ILS is a frequency-limited method while the latter three are capable of full-spectrum calibration. The simulations were performed assuming Beer's law holds and that spectral measurement errors and concentration errors associated with the reference method are normally distributed. Eight different factors that could affect the relative performance of the calibration methods were varied in a two-level, eight-factor experimental design in order to evaluate their effect on the prediction abilities of the four methods. It is found that each of the three full-spectrum methods has its range of superior performance. The frequency-limited ILS method was never the best method, although in the presence of relatively large concentration errors it sometimes yields comparable analysis precision to the full-spectrum methods for the major spectral component. The importance of each factor in the absolute and relative performances of the four methods is compared.

• OSTI ID: 6279672
• Journal Information: Analytical Chemistry (Washington); (USA), Journal Name: Analytical Chemistry (Washington); (USA) Vol. 62:10; ISSN 0003-2700; ISSN ANCHA
• Country of Publication: United States
• Language: English

Related Subjects

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY
400102* -- Chemical & Spectral Procedures
CALIBRATION
CHEMICAL ANALYSIS
LEAST SQUARE FIT
MATHEMATICS
MAXIMUM-LIKELIHOOD FIT
MONTE CARLO METHOD
MULTIVARIATE ANALYSIS
NUMERICAL SOLUTION
QUANTITATIVE CHEMICAL ANALYSIS
SIMULATION
SPECTROSCOPY
STATISTICS