Global and local PLS regression models to predict vapor pressure
Öberg, T., Liu, T.
QSAR & Combinatorial Science 27, 273-279 (2008).
Abstract
The vapor pressure is a key property in determining the distribution and fate of
environmentally relevant compounds, but experimental determinations are only
available for a limited number of the chemicals in current commercial use.
Despite experimental efforts there is a need for estimation methods. The liquid
or subcooled liquid vapor pressures at 298.15 K were collected from the
literature for a diverse set of 1,340 organic compounds. Theoretical molecular
descriptors were derived after optimization to low-energy conformations and used
to investigate the performance of global and local quantitative
structure-property relationships (QSPR). A global PLSR model with ten latent
variables was found to be optimal. The predictive performance of this model,
within the domain of applicability, was estimated at n= 420, Q2Ext = 0.980 and
RMSEP = 0.410 (log Pa). This model can be used in conjunction with other
estimation models to assess the potential for a long range atmospheric
transport.
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