6533b837fe1ef96bd12a1fec

RESEARCH PRODUCT

New cut-off criterion for uninformative variable elimination in multivariate calibration of near-infrared spectra for the determination of heroin in illicit street drugs.

Guillermo QuintásJulia KuligowskiJavier MorosSalvador GarriguesMiguel De La Guardia

subject

Multivariate analysisModels StatisticalSpectroscopy Near-InfraredChemistryIllicit DrugsRepeatabilityBiochemistryAnalytical ChemistryChemometricsHeroinModels ChemicalPartial least squares regressionStatisticsCalibrationCalibrationRange (statistics)Environmental ChemistryCluster AnalysisComputer SimulationVariable eliminationSpectroscopyQuantile

description

A new cut-off criterion has been proposed for the selection of uninformative variables prior to chemometric partial least squares (PLS) modelling. After variable elimination, PLS regressions were made and assessed comparing the results with those obtained by PLS models based on the full spectral range. To assess the prediction capabilities, uninformative variable elimination (UVE)-PLS and PLS were applied to diffuse reflectance near-infrared spectra of heroin samples. The application of the proposed new cut-off criterion, based on the t-Students distribution, provided similar predictive capabilities of the PLS models than those obtained using the original criteria based on quantile value. However, the repeatability of the number of selected variables was improved significantly.

10.1016/j.aca.2008.10.024https://pubmed.ncbi.nlm.nih.gov/19012826