Uses of Interface
edu.cmu.tetrad.algcomparison.algorithm.TakesCovarianceMatrix
Packages that use TakesCovarianceMatrix
Package
Description
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Uses of TakesCovarianceMatrix in edu.cmu.tetrad.algcomparison.algorithm.cluster
Classes in edu.cmu.tetrad.algcomparison.algorithm.cluster that implement TakesCovarianceMatrix -
Uses of TakesCovarianceMatrix in edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag
Classes in edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag that implement TakesCovarianceMatrixModifier and TypeClassDescriptionclass
BOSS (Best Order Score Search)class
Conservative PC (CPC).class
Fast Adjacency Search (FAS)--i.e., the PC adjacency step, which is used in many algorithms.class
FGES (the heuristic version).class
FGES-MB (the heuristic version).class
GRaSP (Greedy Relaxations of Sparsest Permutation)class
Peter/Clark algorithm (PC).class
PC.class
PC.class
SP (Sparsest Permutation) -
Uses of TakesCovarianceMatrix in edu.cmu.tetrad.algcomparison.algorithm.oracle.pag
Classes in edu.cmu.tetrad.algcomparison.algorithm.oracle.pag that implement TakesCovarianceMatrixModifier and TypeClassDescriptionclass
Adjusts GFCI to use a permutation algorithm (such as BOSS-Tuck) to do the initial steps of finding adjacencies and unshielded colliders.class
This class represents the LV-Lite algorithm, which is an implementation of the GFCI algorithm for learning causal structures from observational data using the BOSS algorithm as an initial CPDAG and using all score-based steps afterward.class
This class represents the LV-Lite algorithm, which is an implementation of the GFCI algorithm for learning causal structures from observational data using the BOSS algorithm as an initial CPDAG and using all score-based steps afterward.class
CCD (Cyclic Causal Discovery)class
Conservative FCI.class
The Fast Causal Inference (FCI) algorithm.class
FCI-Max algorithm.class
The Gfci class represents the Greedy Fast Causal Inference algorithm.class
Adjusts GFCI to use a permutation algorithm (such as BOSS-Tuck) to do the initial steps of finding adjacencies and unshielded colliders.class
This class represents the LV-Lite algorithm, which is an implementation of the GFCI algorithm for learning causal structures from observational data using the BOSS algorithm as an initial CPDAG and using all score-based steps afterward.class
RFCI.class
Adjusts GFCI to use a permutation algorithm (in this case SP) to do the initial steps of finding adjacencies and unshielded colliders.class
The SvarFci class is an implementation of the SVAR Fast Causal Inference algorithm.class
SvarGfci class is an implementation of the SVAR GFCI algorithm.