  Uncertainties in nuclear models have a major impact on simulations that aim
at understanding the origin of heavy elements in the universe through the rapid
neutron capture process ($r$ process) of nucleosynthesis. Within the framework
of the nuclear density functional theory, we use results of Bayesian
statistical analysis to propagate uncertainties in the parameters of energy
density functionals to the predicted $r$-process abundance pattern, by way not
only of the nuclear masses but also through the influence of the masses on
$\beta$-decay and neutron capture rates. We additionally make the first
identifications of specific parameters of Skyrme-like energy density
functionals which are correlated with particular aspects of the $r$-process
abundance pattern. While previous studies have explored the reduction in the
abundance pattern uncertainties due to anticipated new measurements of
neutron-rich nuclei, here we point out that an even larger reduction will occur
when these new measurements are used to reduce the uncertainty of model
predictions of masses, which are then propagated through to the abundance
pattern. We make a quantitative prediction for how large this reduction will
be.
