In organic chemistry, atoms other than carbon and hydrogen are generally referred to as heteroatoms. The most common heteroatoms are nitrogen, oxygen and sulfur. Now I present to you an article called Statistical Modeling of a Ligand Knowledge Base, published in 2006-12-31, which mentions a compound: 175136-62-6, mainly applied to statistical analysis linear regression ligand phosphorus, Safety of Tris(3,5-bis(trifluoromethyl)phenyl)phosphine.
A range of different statistical models has been fitted to exptl. data for the Tolman electronic parameter (TEP) based on a large set of calculated descriptors in a prototype ligand knowledge base (LKB) of phosphorus(III) donor ligands. The models have been fitted by ordinary least squares using subsets of descriptors, principal component regression, and partial least squares which use variables derived from the complete set of descriptors, least angle regression, and the least absolute shrinkage and selection operator. None of these methods is robust against outliers, so we also applied a robust estimation procedure to the linear regression model. Criteria for model evaluation and comparison have been discussed, highlighting the importance of resampling methods for assessing the robustness of models and the scope for making predictions in chem. intuitive models. For the ligands covered by this LKB, ordinary least squares models of descriptor subsets provide a good representation of the data, while partial least squares, principal component regression, and least angle regression models are less suitable for our dual aims of prediction and interpretation. A linear regression model with robustly fitted parameters achieves the best model performance over all classes of models fitted to TEP data, and the weightings assigned to ligands during the robust estimation procedure are chem. intuitive. The increased model complexity when compared to the ordinary least squares linear model is justified by the reduced influence of individual ligands on the model parameters and predictions of new ligands. Robust linear regression models therefore represent the best compromise for achieving statistical robustness in simple, chem. meaningful models.
After consulting a lot of data, we found that this compound(175136-62-6)Safety of Tris(3,5-bis(trifluoromethyl)phenyl)phosphine can be used in many types of reactions. And in most cases, this compound has more advantages.
Reference:
Piperidine – Wikipedia,
Piperidine | C5H11N – PubChem