SYSTEMS AND METHODS FOR IDENTIFYING CORRELATED VARIABLES IN LARGE AMOUNTS OF SPECTROMETRY DATA

摘要

Groups of correlated representations of variables are identified from a large amount of spectrometry data. A plurality of samples is analyzed and a plurality of measured variables is obtained from a spectrometer. A processor executes a number of steps. The plurality of measured variables is divided into a plurality of measured variable subsets. Principal component analysis followed by variable grouping (PCVG) is performed on each measured variable subset, producing one or more group representations for each measured variable subset and a plurality of group representations for the plurality of measured variable subsets. While the total number of the plurality of group representations is greater than a maximum number, the plurality of group representations is divided into a plurality of representative subsets and PCVG is performed on each subset. PCVG is performed on the remaining the plurality of group representations, producing a plurality of groups of correlated representations of variables.