  We introduce a novel unbiased, cross-correlation estimator for the one-point
statistics of cosmological random fields. One-point statistics are a useful
tool for analysis of highly non-Gaussian density fields, while
cross-correlations provide a powerful method for combining information from
pairs of fields and separating them from noise and systematics. We derive a new
Deconvolved Distribution Estimator that combines the useful properties of these
two methods into one statistic. Using two example models of a toy Gaussian
random field and a line intensity mapping survey, we demonstrate these
properties quantitatively and show that the DDE can be used for inference. This
new estimator can be applied to any pair of overlapping, non-Gaussian
cosmological observations, including large-scale structure, the
Sunyaev-Zeldovich effect, weak lensing, and many others.
