Multivariate exploratory data analysis in chemical industry

Sizeable data bases are now being routinely generated in a variety of contexts in chemical industry. Statistical investigations of such data bases are aimed both at initially uncovering structure and eventually proposing models, in particular for predicting product quality by the mix or characteristics of the chemical compounds. Online Multivariate Exploratory Graphical Analysis (OMEGA) stands for a structured exploratory study of the relationships in a multivariate data set, where, rather than testing for one specific property, as many clues as possible for interesting structures are searched for by different dimension reductions and succeeding interactive graphical analyses. The stability of the projections obtained by the different dimension reduction methods is assessed by simulation producing graphical displays particularly supporting the identification of influential points. The variation of the predictions obtained by the different dimension reduction methods is assessed by cross-validation delivering misclassification rates or cross-validated R² values. The interpretation of the new coordinates corresponding to dimension reduction is supported by loading simplifications and graphical displays for judging its adequacy. The OMEGA strategy has been found to be an effective tool for routine searching for structure.