gAlgo-class


  <code>"gAlgo"</code> is a <code>"VIRTUAL"</code> class, the common basis of classes
  <code>"pcAlgo"</code> and <code>"fciAlgo"</code>.<p></p><p>  We describe the common slots here; for more see the help pages of the
  specific classes.
</p>

classes

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 data from observational studies
(i.e. observational data) and data from experiments
involving interventions (i.e. interventional data) without hidden
variables). For causal inference the IDA algorithm, the Generalized
Backdoor Criterion (GBC) and the Generalized Adjustment Criterion (GAC)
are implemented.

Markus Kalisch

pcalg

Methods for Graphical Models and Causal Inference

gAlgo-class function

Slots


  <code>"gAlgo"</code> is a <code>"VIRTUAL"</code> class, the common basis of classes
  <code>"pcAlgo"</code> and <code>"fciAlgo"</code>.

  We describe the common slots here; for more see the help pages of the
  specific classes.


gAlgo-class: Class `"gAlgo"`

Description

Arguments

Slots

See Also

Examples