  Principal Component Analysis (PCA) is a well-known multivariate technique
used to decorrelate a set of vectors. PCA has been extensively applied in the
past to the classification of stellar and galaxy spectra. Here we apply PCA to
the optical spectra of early-type galaxies, with the aim of extracting
information about their star formation history. We consider two different data
sets: 1) a reduced sample of 30 elliptical galaxies in Hickson compact groups
and in the field, and 2) a large volume-limited (z<0.1) sample of ~7,000
galaxies from the Sloan Digital Sky Survey. Even though these data sets are
very different, the homogeneity of the populations results in a very similar
set of principal components. Furthermore, most of the information (in the sense
of variance) is stored into the first few components in both samples. The first
component (PC1) can be interpreted as an old population and carries over 99% of
the variance. The second component (PC2) is related to young stars and we find
a correlation with NUV flux from GALEX. Model fits consistently give younger
ages for those galaxies with higher values of PC2.
