has_specified_output achieves_planned_objective clustered data set regression analysis method principal component regression The Principal Component Regression method is a regression analysis method that combines the Principal Component Analysis (PCA)spectral decomposition with an Inverse Least Squares (ILS) regression method to create a quantitative model for complex samples. Unlike quantitation methods based directly on Beer's Law which attempt to calculate the absorbtivity coefficients for the constituents of interest from a direct regression of the constituent concentrations onto the spectroscopic responses, the PCR method regresses the concentrations on the PCA scores. Tina Hernandez-Boussard WEB: : http://www.thermo.com/com/cda/resources/resources_detail/1,2166,13414,00.html principal component regression class discovery data transformation class discovery objective pending final vetting obi.owl