Analyzing Principal Components and Reducing Dimensionality
Using the Principal Components Platform
The purpose of principal component analysis is to derive a small number of independent linear combinations (principal components) of a set of variables that capture as much of the variability in the original variables as possible.
JMP also offers several types of orthogonal and oblique Factor-Analysis-Style rotations to help interpret the extracted components. The platform also supports factor analysis.
Principal components can be accessed through the Multivariate platform, through the Scatterplot 3D platform, or through the Principal Components command on the Analyze > Multivariate Methods menu. All map to the same routines, documented ...