In order to compute the probability of causality, we must first fit the data to our model. We accomplish this through a maximum likelihood estimation over . The formulation of our approach lends itself to the standard Expectation Maximization (EM) algorithm. The E-step of the EM involves computing at each locus independently, the posterior probability of each using an application of Bayes Theorem:(4)
