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Second‐order regression of 13 C substituent chemical shifts with Taft's sigma constants
Author(s) -
Holik Miroslav
Publication year - 1992
Publication title -
magnetic resonance in chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.483
H-Index - 72
eISSN - 1097-458X
pISSN - 0749-1581
DOI - 10.1002/mrc.1260300302
Subject(s) - substituent , chemistry , linear regression , principal component analysis , chemical shift , sigma , resonance (particle physics) , stereochemistry , computational chemistry , mathematics , statistics , quantum mechanics , physics
In addition to Taft's dual substituent parameter (DSP) and DSP–non–linear resonance (DSP–NLR) models, and Charton's triple substituent parameter (TSP) equation, two second‐order regression models were tested using published data for 13 C substituent chemical shifts of the C‐4 atom in 1,4‐disubstituted benzenes. The complete data matrix consisted of 14 series with a fixed Y (C‐4) substituent, each with 14 variable X (C‐1) substituents. Second‐order (in the σ R Oparameter or in a combination of the σ 1 and σ R Oconstants) models gave results as good as, and in some cases even better than, the DSP–NLR equation; the results of the TSP model were always worse. The whole data matrix was submitted to principal component analysis. Target testing has shown vectors of σ R O , (σ R O ) 2 and σ I constants as ‘real’ principal components.