This data set contains a matrix containing information on five
  discrete variables (levels are coded as numbers) and the corresonding
  DAG model.

datasets

This package contains several functions for causal structure
  learning and causal inference using graphical models. The main algorithms
  for causal structure learning are PC (for observational data without hidden
  variables), FCI and RFCI (for observational data with hidden variables),
  and GIES (for a mix of observational and interventional data without hidden
  variables). For causal inference the IDA algorithm and the generalized
  backdoor criterion is implemented.

gmD: Graphical Model Discrete 5-Dim Example Data

Description

Usage

Arguments

Details

Examples