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

Article ID

3LO1H

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

Fatiha Mebarki
Fatiha Mebarki University Badji Mokhtar Annaba
Khadidja Amirat
Khadidja Amirat
Salima Ali Mokhnache
Salima Ali Mokhnache
Djelloul Messadi
Djelloul Messadi
DOI

Abstract

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 approximate.

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 approximate.

Fatiha Mebarki
Fatiha Mebarki University Badji Mokhtar Annaba
Khadidja Amirat
Khadidja Amirat
Salima Ali Mokhnache
Salima Ali Mokhnache
Djelloul Messadi
Djelloul Messadi

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Fatiha Mebarki. 2016. “. Global Journal of Human-Social Science – B: Geography, Environmental Science & Disaster Management GJHSS-B Volume 16 (GJHSS Volume 16 Issue B1): .

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Crossref Journal DOI 10.17406/GJHSS

Print ISSN 0975-587X

e-ISSN 2249-460X

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GJHSS Volume 16 Issue B1
Pg. 17- 26
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GJHSS-B Classification: FOR Code: 300899p
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Modeling Retention Indices of a Series Components Food and Pollutants of the Environment: Methods; OLS, LAD

Fatiha Mebarki
Fatiha Mebarki University Badji Mokhtar Annaba
Khadidja Amirat
Khadidja Amirat
Salima Ali Mokhnache
Salima Ali Mokhnache
Djelloul Messadi
Djelloul Messadi

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