R6 Class for Structural Causal Models
Simulate data from a conditional linear Gaussian SCM
Return the mean and the covariance matrix of the conditional distribut...
SCM "backdoor" used in the examples.
SCM "backdoor_md" used in the examples.
Counterfactual inference via simulation
SCM "credit" used in the credit scoring example.
Checking fairness of a prediction via counterfactual simulation
SCM "frontdoor" used in the examples.
Define structural function by a conditional probability table
R6 Class for linear structural causal models where background variable...
R6 Class for parallel world models
R6causal: R6 Class for Structural Causal Models
R6causal: R6 class for structural causal models
Conduct a sequence of interventions and collect the simulated data.
R6 Class for structural causal models
SCM "trapdoor" used in the examples.
The implemented R6 class 'SCM' aims to simplify working with structural causal models. The missing data mechanism can be defined as a part of the structural model. The class contains methods for 1) defining a structural causal model via functions, text or conditional probability tables, 2) printing basic information on the model, 3) plotting the graph for the model using packages 'igraph' or 'qgraph', 4) simulating data from the model, 5) applying an intervention, 6) checking the identifiability of a query using the R packages 'causaleffect' and 'dosearch', 7) defining the missing data mechanism, 8) simulating incomplete data from the model according to the specified missing data mechanism and 9) checking the identifiability in a missing data problem using the R package 'dosearch'. In addition, there are functions for running experiments and doing counterfactual inference using simulation.