Replicate analysis and outlier detection in multivariate NIR calibration, illustrated with biofuel analysis
A biofuel data set is used to show multivariate calibration and prediction of the vital parameter moisture content from near-infrared spectra. At-line sampling of heterogeneous biofuel materials and near-infrared spectroscopy (1050 wavelengths) gave prediction errors of 3 and 1% for the moisture ref...
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| Veröffentlicht in: | Analytica chimica acta 2005-07, Vol.544 (1), p.177-183 |
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| container_title | Analytica chimica acta |
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| creator | Lillhonga, Tom Geladi, Paul |
| description | A biofuel data set is used to show multivariate calibration and prediction of the vital parameter moisture content from near-infrared spectra. At-line sampling of heterogeneous biofuel materials and near-infrared spectroscopy (1050 wavelengths) gave prediction errors of 3 and 1% for the moisture reference. The calibration methodology and prediction diagnostics are presented in the paper with an emphasis of using replicates and duplicates for outlier detection. |
| doi_str_mv | 10.1016/j.aca.2005.01.057 |
| format | Article |
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| ispartof | Analytica chimica acta, 2005-07, Vol.544 (1), p.177-183 |
| issn | 0003-2670 1873-4324 |
| language | eng |
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| source | Elsevier ScienceDirect Journals |
| subjects | Analytical chemistry At-line Chemistry Exact sciences and technology Moisture Multivariate calibration Natural variability Near-infrared spectroscopy Off-line Outlier statistics Prediction Spectrometric and optical methods |
| title | Replicate analysis and outlier detection in multivariate NIR calibration, illustrated with biofuel analysis |
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