# Significance Test for Jaccard Distance

I am looking for a significance test for the Jaccard Distance (JD).

As an example, I have two datasets as follows:

Baseline: $\left| A\bigcap B \right|=57;\ \left| A\bigcup B \right|=275\quad \therefore \ JD=0.7927$

Evaluation: $\left| A\bigcap B \right|=126;\ \left| A\bigcup B \right|=433\quad \therefore \ JD=0.7090$

Is there a way to determine whether the JD at evaluation is significantly different from the baseline?

Or do I simply use the classical z-test of proportions? The z-test assumes that there is a significant difference from the baseline.

Given two input vectors, its main function, jaccard.test(), computes a p-value. If your data is too big, the exact solution (accessed through method = "exact") could be slow and you may want to use a fast and accurate estimation (access through method = "mca").