  We build a four-dimensional linear model of object membership in the Beta
Pictoris moving group (BPMG), using two nested applications of Principal
Component Analysis (PCA) to high-quality data on about 1.5 million objects.
These data contain the objects' galactic space velocities and also their Gaia
$G$ magnitudes. Through PCA, they ultimately result in a four-dimensional
straight line, referred to as PC $1'$, about which both the bona fide members
used to obtain the straight line and the candidate members used to test the
model congregate at generally small distances. Our bona fide members come from
a recent, Gaia DR2-based compilation. Most candidate members are from a
compilation from 2017. Using a standard procedure to flag groups of outliers in
data sets, we argue that flagging the few possible outliers we identified on
account of distances to PC $1'$ is consistent with the nature of the candidate
members in use. The spatial and kinematic measurements that backed their
inclusion in the 2017 compilation were of course from before the availability
of data from the Gaia mission. Moreover, their radial velocities at the time
were either unknown or estimated somewhat unreliably. We propose that PC $1'$
be added to the tool set for BPMG analyses and potentially extended to other
young stellar moving groups.
