CausalModel
CausalModel is a framework for representing causal relationships among variables, enabling reasoning about interventions and counterfactuals. It formalizes how outcomes arise from mechanisms and can be used to predict the effects of actions in a system.
The most common formalization is the structural causal model (SCM). An SCM consists of endogenous variables,
Inference tasks include determining whether a causal effect is identifiable from observed data, using rules such
Learning from data involves estimating the structural equations and sometimes the graph, using observational data, randomized
Causal models underpin many fields, including epidemiology, economics, and machine learning, and inform policy decisions, causal