  We reconstruct posterior distributions for the position (sky area and
distance) of a simulated set of binary neutron-star gravitational-waves signals
observed with Advanced LIGO and Advanced Virgo. We use a Dirichlet Process
Gaussian-mixture model, a fully Bayesian non-parametric method that can be used
to estimate probability density functions with a flexible set of assumptions.
The ability to reliably reconstruct the source position is important for
multimessenger astronomy, as recently demonstrated with GW170817. We show that
for detector networks comparable to the early operation of Advanced LIGO and
Advanced Virgo, typical localization volumes are
$\sim10^4$--$10^5~\mathrm{Mpc^3}$ corresponding to $\sim10^2$--$10^3$ potential
host galaxies. The localization volume is a strong function of the network
signal-to-noise ratio, scaling roughly $\propto \varrho_{net}^{-6}$. Fractional
localizations improve with the addition of further detectors to the network.
Our Dirichlet Process Gaussian-mixture model can be adopted for localizing
events detected during future gravitational-wave observing runs, and used to
facilitate prompt multimessenger follow-up.
