Using these two corollaries, it is therefore possible to accurately compute the p-value of the event or of its complementary with a complexity O(L + ζ) in memory and O(n × ζ) in time where ζ is the number of non zero terms in the matrix R. In the worst case, ζ = (L - 1)2 but the technique of FMCI usually leads to a very sparse structure for R. One should note that these dramatic improvements from the naive approach could even get better by considering the structure of R itself, but this have to be done specifically for each considered problem. We will give detailed examples of this in both our application parts but, for the moment, we focus on the general case for which we give algorithms.