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Multiple regression analysis with optimal molecular descriptors
1Department of Mathematics and Computer Science, Drake University, Des Moines, IA 50311, USA.
Abstract:
We consider construction of optimal molecular descriptors to be used for multiple regression analysis of several properties of alcohols. The descriptors are obtained by considering shorter paths with variable weight x for carbon-oxygen bond in alcohol. In particular we consider as molecular descriptors paths of length 1, 2 and 3. The multiple regression analysis of the following molecular properties was examined: - log S (S = solubility), CSA (cavity surface area), log P (P = octanol/water partition), and log gamma (gamma = infinite solution activity coefficient). By minimizing the standard error of the regression for each property we found optimal variable weight.
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