Approximating majority depth

We consider the problem of approximating the majority depth (Liu and Singh, 1993) of a point q with respect to an n-point set, S, by random sampling. At the heart of this problem is a data structures question: How can we preprocess a set of n   lines so that we can quickly test whether a randomly selected vertex in the arrangement of these lines is above or below the median level. We describe a Monte Carlo data structure for this problem that can be constructed in O(nlogn) time, can answer queries in O((logn)4/3) expected time, and answers correctly with high probability.