%0 DATA
%A Lailong, Mu
%A Hongmei, He
%A Weihua, Yang
%A Changjun, Feng
%D 2009
%T Variable Molecular Connectivity Indices for Predicting the Diamagnetic Susceptibilities of Organic Compounds
%U https://acs.figshare.com/articles/Variable_Molecular_Connectivity_Indices_for_Predicting_the_Diamagnetic_Susceptibilities_of_Organic_Compounds/2863948
%R 10.1021/ie801252j.s001
%2 https://acs.figshare.com/ndownloader/files/4561774
%K literature methods
%K molar diamagnetic susceptibilities
%K AAD
%K subsets regression analysis method
%K 4.37 cgs
%K results show
%K 3.72 cgs
%K connectivity
%K adjacency matrix
%K compound
%K molar diamagnetic susceptibility
%K Diamagnetic Susceptibilities
%K Organic CompoundsFor
%K MLR model
%K optimization methods
%K correlation coefficient r
%K Variable Molecular Connectivity Indices
%X For predicting the molar diamagnetic susceptibilities of organic compounds, a variable molecular connectivity index ^{m}*χ*′ and its converse index ^{m}*χ*′′ based on the adjacency matrix of molecular graphs and the variable atomic valence connectivity index δ_{i}′ were proposed. The optimal values of parameters *a*, *b*, and *y* included in definition of δ_{i}′, ^{m}*χ*′ and ^{m}*χ*′′ can be found by optimization methods. When *a* = 1.10, *b* = 2.8, and *y* = 0.36, a good five-parameter model can be constructed from ^{m}*χ*′ and ^{m}*χ*′′ by using the best subsets regression analysis method for the molar diamagnetic susceptibilities of organic compounds. The correlation coefficient *r*, standard error *s*, and average absolute deviation (AAD) of the multivariate linear regression (MLR) model are 0.9930, 4.99, and 3.72 cgs, respectively, for the 720 organic compounds (training set). The AAD of predicted values of the molar diamagnetic susceptibility of another 361 organic compounds (test set) is 4.37 cgs for the MLR model. The results show that the current method is more effective than literature methods for estimating the molar diamagnetic susceptibility of an organic compound.