  The authors transpose a discrete notion of indetermination coupling in the
case of continuous probabilities. They show that this coupling, expressed on
densities, cannot be captured by a specific copula which acts on cumulative
distribution functions without a high dependence on the margins. Furthermore,
they define a notion of average likelihood which extends the discrete notion of
couple matchings and demonstrate it is minimal under indetermination.
Eventually, they leverage this property to build up a statistical test to
distinguish indetermination and estimate its efficiency using the Bahadur's
slope.
