A maximum entropy estimate of uncertainty about a wine rating

Abstract

Much research shows that the ratings that judges assign to the same wine are uncertain. And while the ratings may be independent, research also shows that they are not identically distributed. Thus, an acute difficulty in ratings-related research and in calculating consensus among judges is that each rating is one observation drawn from a latent distribution that is wine- and judge-specific. What can be deduced about the shape of a latent distribution from one observation? A simple maximum entropy estimator is proposed to describe the distribution of a rating observed. The estimator can express the implications of zero, one, a few blind replicates, and many observations. Several tests of the estimator show that results are consistent with the results of experiments with blind replicates and that results are more accurate than results based on observed ratings alone.