Application of Maximum Likelihood Principal Components Regression to Fluorescence Emission Spectra

Abstract

The application of maximum likelihood multivariate calibration methods to the  uorescence emission spectra of mixtures of acenaphthylene, naphthalene, and phenanthrene in acetonitrile is described. Maximum likelihood principal components regression (MLPCR) takes into account the measurement error structure in the spectral data in constructing the… (More)

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@inproceedings{Schreyer2004ApplicationOM, title={Application of Maximum Likelihood Principal Components Regression to Fluorescence Emission Spectra}, author={Suzanne K. Schreyer and Michael A Bidinosti}, year={2004} }