Constrained probability distributions of correlation functions
  Context: Two-point correlation functions are used throughout cosmology as a
measure for the statistics of random fields. When used in Bayesian parameter
estimation, their likelihood function is usually replaced by a Gaussian
approximation. However, this has been shown to be insufficient.
  Aims: For the case of Gaussian random fields, we search for an exact
probability distribution of correlation functions, which could improve the
accuracy of future data analyses.
  Methods: We use a fully analytic approach, first expanding the random field
in its Fourier modes, and then calculating the characteristic function.
Finally, we derive the probability distribution function using integration by
residues. We use a numerical implementation of the full analytic formula to
discuss the behaviour of this function.
  Results: We derive the univariate and bivariate probability distribution
function of the correlation functions of a Gaussian random field, and outline
how higher joint distributions could be calculated. We give the results in the
form of mode expansions, but in one special case we also find a closed-form
expression. We calculate the moments of the distribution and, in the univariate
case, we discuss the Edgeworth expansion approximation. We also comment on the
difficulties in a fast and exact numerical implementation of our results, and
on possible future applications.
