Class SpFci

java.lang.Object
edu.cmu.tetrad.search.SpFci
All Implemented Interfaces:
IGraphSearch

public final class SpFci extends Object implements IGraphSearch
Uses SP in place of FGES for the initial step in the GFCI algorithm. This tends to produce an accurate PAG than GFCI as a result, for the latent variables case. This is a simple substitution; the reference for GFCI is here:

J.M. Ogarrio and P. Spirtes and J. Ramsey, "A Hybrid Causal Search Algorithm for Latent Variable Models," JMLR 2016. Here, SP has been substituted for FGES.

The reference for the SP algorithm is here:

Raskutti, G., & Uhler, C. (2018). Learning directed acyclic graph models based on sparsest permutations. Stat, 7(1), e183.

For SP only a score is needed, but there are steps in GFCI that require a test, so for this method, both a test and a score need to be given.

Note that SP considers all permutations of the algorithm, which is exponential in the number of variables. So SP is limited to about 10 variables.

This class is configured to respect knowledge of forbidden and required edges, including knowledge of temporal tiers.

Version:
$Id: $Id
Author:
josephramsey, bryan andrews
See Also: