1988
DOI: 10.1021/ac00163a018
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Chemometrics

Abstract: 02) Gouveia, M. A.; Seabra e Barros, J.; Tavares, M. J.; Freitas, M. C. J (G4) Routh, M. W. Spectroscopy 1987, 2, 45-52. (G5) Ottaway, J. M.; Littlejohn, D.; Marshall, J. Fortschr. Atomspektrom. (G6) Matuslewlcz, H. Chem. Inz. Chem. 1986, 76, 75-90. (G7) Willoughby, E. J. Commun. Sol Scl. Plant Anal. 1986. 77, 667-677. (G8) Sanz-Medel, A.; Rodriguez Roza, R.; Gonzalez Alonso, R.; Nova1 Valli-(G9) Kratochvil, B.; Motkosky, N.; Duke, M. J. M.: Ng., D. Can. J . Chem.the detailed discussion of computers is somewha… Show more

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Cited by 69 publications
(9 citation statements)
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“…In addition, the development of the algorithms intended to interpret these results and to assist in the deconvolution of overlapped spectral features in mixtures is an active and important research field. [63][64][65][66][67]…”
Section: The Rotational Fingerprint In Analytical Applicationsmentioning
confidence: 99%
“…In addition, the development of the algorithms intended to interpret these results and to assist in the deconvolution of overlapped spectral features in mixtures is an active and important research field. [63][64][65][66][67]…”
Section: The Rotational Fingerprint In Analytical Applicationsmentioning
confidence: 99%
“…Models containing four factors for the individual sample groups from the database containing only measurable species reveal the expected pH-sensitive factor and reactant factors for Table 9. pH-sensitive factor loadings for acids and bases from data matrices modelled after groups 1 cadmium, zinc and iron(I1). In the six-factor model, reactant factors for pyridine and chloride appear, while the metal reactant factors and the pH-sensitive factor closely resemble those of the four-factor model.…”
Section: Database Containing Only Measurable Speciesmentioning
confidence: 99%
“…Quantitative structure−activity relationship (QSAR) correlations have been widely applied for biological activities over several decades. Also, many applications of quantitative structure−property relationships (QSPR) are known in analytical chemistry. ,− For instance, we recently successfully used our CODESSA ( Comprehensive Descriptors for Structural and Statistical Analysis ) QSPR program to achieve the first comprehensive correlation of both GC retention times and response factors for a large and widely diversified set of organic compounds. The QSPR equations developed 15 allow the prediction of each of these two quantities for unknown compounds with significant confidence.…”
Section: Introductionmentioning
confidence: 99%