We present the Total Conditioning (TC) algorithm for causal discovery suited in the presence of continuous variables. Given a set of n data points drawn from a distribution whose underlying causal structure is a directed acyclic graph (DAG), the TC algorithm returns a structure, i.e., a DAG, over the variables that tends to the correct structure when n tends to infinity. The approach builds on the structural equation modeling framework, well suited for continuous variables, and relies on causal… CONTINUE READING