Non-Gaussian inference from non-linear and non-Poisson biased
  distributed data
  We study the statistical inference of the cosmological dark matter density
field from non-Gaussian, non-linear and non-Poisson biased distributed tracers.
We have implemented a Bayesian posterior sampling computer-code solving this
problem and tested it with mock data based on N-body simulations.
