Noise-marginalized optimal statistic: A robust hybrid
  frequentist-Bayesian statistic for the stochastic gravitational-wave
  background in pulsar timing arrays
  Observations have revealed that nearly all galaxies contain supermassive
black holes (SMBHs) at their centers. When galaxies merge, these SMBHs form
SMBH binaries (SMBHBs) that emit low-frequency gravitational waves (GWs). The
incoherent superposition of these sources produce a stochastic GW background
(GWB) that can be observed by pulsar timing arrays (PTAs). The optimal
statistic is a frequentist estimator of the amplitude of the GWB that
specifically looks for the spatial correlations between pulsars induced by the
GWB. In this paper, we introduce an improved method for computing the optimal
statistic that marginalizes over the red noise in individual pulsars. We use
simulations to demonstrate that this method more accurately determines the
strength of the GWB, and we use the noise-marginalized optimal statistic to
compare the significance of monopole, dipole, and Hellings-Downs (HD) spatial
correlations and perform sky scrambles.
