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 TypeClassDescriptionclassBOSS (Best Order Score Search)classConservative PC (CPC).classFast Adjacency Search (FAS)--i.e., the PC adjacency step, which is used in many algorithms.classFGES (the heuristic version).classFGES-MB (the heuristic version).classGRaSP (Greedy Relaxations of Sparsest Permutation)classPeter/Clark algorithm (PC).classPC.classPC.classSP (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 TypeClassDescriptionclassAdjusts GFCI to use a permutation algorithm (such as BOSS-Tuck) to do the initial steps of finding adjacencies and unshielded colliders.classThis 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.classThis 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.classCCD (Cyclic Causal Discovery)classConservative FCI.classThe Fast Causal Inference (FCI) algorithm.classFCI-Max algorithm.classThe Gfci class represents the Greedy Fast Causal Inference algorithm.classAdjusts GFCI to use a permutation algorithm (such as BOSS-Tuck) to do the initial steps of finding adjacencies and unshielded colliders.classThis 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.classRFCI.classAdjusts GFCI to use a permutation algorithm (in this case SP) to do the initial steps of finding adjacencies and unshielded colliders.classThe SvarFci class is an implementation of the SVAR Fast Causal Inference algorithm.classSvarGfci class is an implementation of the SVAR GFCI algorithm.