Patent ID: 7587285

Claim:
A method for identifying correlated variables, comprising: analyzing a plurality of samples using a spectrometer; producing a plurality of variables from the plurality of samples using the spectrometer; obtaining the plurality of variables from the spectrometer using a processor; performing principal component analysis on the plurality of variables using the processor; selecting a number of principal components produced by the principal component analysis using the processor; creating a subset principal component space having the number of principal components using the processor; selecting a variable in the subset principal component space using the processor; defining a spatial angle around a vector extending from an origin to the variable using the processor; selecting a set of one or more variables within the spatial angle of the vector using the processor; and assigning the set to a group using the processor, if the set comprises a minimum number of variables, wherein the group identifies correlated variables and wherein the minimum number of variables is a number of correlated variables a group is expected to include.