Modeling Retention Indices of a Series Components Food and Pollutants of the Environment: Methods; OLS, LAD

The gas chromatographic retention indices for 89 pyrazines of test and 25 of validation on O V-101 and Carbowax -20M are successfuty modeled with the ald of a computer and the Software system Structural descriptors are calculated and multiple linear regression analysis are used to generate model equations relating structural features to observed retention characteristics then was treated with two methods The detection of influential observations for the standard least squares regression model is a problem which has been extensively studied LAD regression diagnostics offers alternative dicapproaches whose main feature is the robustness Here a nonparametric method for detecting influential observations is presented and compared with other classical diagnostics methods Comparisons are between models generated for the two stationary was carried out with two methods and descriptors that may encode differences in solute interactions with stationary phases of differing polarity are discussed and validated results in the state approached by the tests statistics Test of Anderson-Darling shapiro-wilk Agostino Jarque-Bera and the confidence interval thanks to the concept of robustness to check if the distribution of the errors is really approximat

Modeling Retention Indices of a Series Components Food and Pollutants of the Environment: Methods; OLS, LAD

The gas chromatographic retention indices for 89 pyrazines of test and 25 of validation on O V-101 and Carbowax -20M are successfuty modeled with the ald of a computer and the Software system Structural descriptors are calculated and multiple linear regression analysis are used to generate model equations relating structural features to observed retention characteristics then was treated with two methods The detection of influential observations for the standard least squares regression model is a problem which has been extensively studied LAD regression diagnostics offers alternative dicapproaches whose main feature is the robustness Here a nonparametric method for detecting influential observations is presented and compared with other classical diagnostics methods Comparisons are between models generated for the two stationary was carried out with two methods and descriptors that may encode differences in solute interactions with stationary phases of differing polarity are discussed and validated results in the state approached by the tests statistics Test of Anderson-Darling shapiro-wilk Agostino Jarque-Bera and the confidence interval thanks to the concept of robustness to check if the distribution of the errors is really approximat