Uses of Interface
edu.cmu.tetrad.algcomparison.algorithm.TakesCovarianceMatrix

Packages that use TakesCovarianceMatrix

Package	Description
edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag
edu.cmu.tetrad.algcomparison.algorithm.oracle.pag

Uses of TakesCovarianceMatrix in edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag

Classes in edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag that implement TakesCovarianceMatrix

Modifier and Type	Class	Description
class	Boss	BOSS (Best Order Score Search)
class	BossCdnodScore	BOSS + score-based CD-NOD context augmentation.
class	BossTopK	BOSS-TopK (Best Order Score Search, Top K).
class	Cdnod	CD-NOD wrapper for algcomparison.
class	CdnodPag	CD-NOD wrapper for algcomparison.
class	Cpc	Conservative PC (CPC).
class	Fas	Fast Adjacency Search (FAS)--i.e., the PC adjacency step, which is used in many algorithms.
class	Fges	FGES (the heuristic version).
class	FgesMb	FGES-MB (the heuristic version).
class	Flop	FLOP (Fast Learning of Order and Parents).
class	Grasp	GRaSP (Greedy Relaxations of Sparsest Permutation)
class	IsFges	IS-FGES (Instance-Specific FGES) wrapper for the algcomparison interface.
class	Pc	Peter/Clark algorithm (PC).
class	PcAr	Peter/Clark algorithm with adjacency-rescue (PcAR): PC augmented with detection, and optionally repair, of cancelled unfaithful-triangle edges.
class	Pcd	PC.
class	PcMax	PC-Max.
class	PcMb	PC.
class	RestrictedBoss	Implements a restricted version of the BOSS (Best Order Score Search) algorithm that focuses search on a set of target variables and their immediate causes.
class	Sp	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 TakesCovarianceMatrix

Modifier and Type	Class	Description
class	Bfci	Adjusts FGES-FCI to use a permutation algorithm (such as BOSS-Tuck) to do the initial steps of finding adjacencies and unshielded colliders.
class	BfciBryan	BFCI-Bryan: BOSS followed by the from-scratch, sepset-map-as-state formulation of the gated StarFCI extra-edge-removal step, with sepset RE-SELECTION (a gate-rejected separating set does not retire the pair; the next separating set is tried) and NO saturating step.
class	BfciBryanScore	BFCI-Bryan-Score: BFCI-Bryan (sepset re-selection under the legality gate) with a scoring step: a legal candidate is committed only if the RICF Gaussian BIC of its MAG strictly improves on the committed model's, following Bryan Andrews's "BFCI-Bryan with scoring" pseudocode.
class	BfciC	Adjusts FGES-FCI to use a permutation algorithm (such as BOSS-Tuck) to do the initial steps of finding adjacencies and unshielded colliders.
class	BfciD	Adjusts FGES-FCI to use a permutation algorithm (such as BOSS-Tuck) to do the initial steps of finding adjacencies and unshielded colliders.
class	BfciScoreCheck	/ Hidden from the interface on 2026-10-21 (no @Algorithm annotation): kept only so that saved sessions
class	BossCcd	BOSS-CCD (Cyclic Causal Discovery with a BOSS adjacency superstructure).
class	BossFci	BOSS-FCI, the former name of BFCI.
class	BossPod	BOSS-POD, removed in Tetrad 8.0.0.
class	Ccd	CCD (Cyclic Causal Discovery)
class	Cfci	CFCI (Conservative FCI).
class	Cpw	Implements the CPW (Cyclic Pairwise) algorithm for causal discovery from continuous, causally sufficient observational data.
class	DmFcit	DM-FCIT, removed in Tetrad 8.0.0.
class	DmPc	DM-PC, removed in Tetrad 8.0.0.
class	Fci	The Fast Causal Inference (FCI) algorithm.
class	FciCyclicPw	FCI-CPW: Run FCI with internally constructed PW-forbidden knowledge, then orient edges using a pairwise left-right rule on standardized data in cases that are safe under no-selection-bias cyclic semantics: Tail–tail (—) edges Orient per pairwise rule. Tail–circle (—o) edges If pairwise prefers x→y, set x→y (symmetrically, if prefers y→x, set y→x). Circle–circle (o–o) edges If pairwise prefers x→y, set x o→y (symmetrically for y→x).
class	FciMax	FCI-Max.
class	Fcit	This class represents the FCI Targeted Testing (FCIT) algorithm, which is variant of the *-FCI algorithm for learning causal structures from observational data using the BOSS algorithm as an initial CPDAG and using all score-based steps afterward.
class	FcitMagMarkov	This class represents the FCI Targeted Testing (FCIT) algorithm, which is variant of the *-FCI algorithm for learning causal structures from observational data using the BOSS algorithm as an initial CPDAG and using all score-based steps afterward.
class	FcitMarkov	This class represents the FCI Targeted Testing (FCIT) algorithm, which is variant of the *-FCI algorithm for learning causal structures from observational data using the BOSS algorithm as an initial CPDAG and using all score-based steps afterward.
class	FcitSl	This class represents the FCI Targeted Testing (FCIT) algorithm, which is variant of the *-FCI algorithm for learning causal structures from observational data using the BOSS algorithm as an initial CPDAG and using all score-based steps afterward.
class	FcitSlScoreCheck	FCIT-SL-Score-Check: the FCIT-SL algorithm with a MAG BIC SCORE CHECK applied to every candidate the search adjudicates.
class	FcitZm	This class represents the FCI Targeted Testing (FCIT) algorithm, which is variant of the *-FCI algorithm for learning causal structures from observational data using the BOSS algorithm as an initial CPDAG and using all score-based steps afterward.
class	Gfci	The Fges-FCI class represents the Greedy Fast Causal Inference algorithm, adjusted as in *-FCI.
class	GfciOld	The GFCI class represents the Greedy Fast Causal Inference algorithm, adjusted as in *-FCI.
class	Gmas	GMAS: a latent-variable search that uses no independence tests.
class	GraspFci	GRaSP-FCI, an implentatation of *-FCI using GRaSP.
class	Icd	The Iterative Causal Discovery (ICD) algorithm.
class	IsGfci	IS-GFCI (Instance-Specific GFCI) wrapper for the algcomparison interface.
class	LvBossExperimental	Wrapper for LV-BOSS: the fully score-based latent-variable search that embeds a MAG projection inside a BOSS-style search over orders, scored by the exact RICF Gaussian MAG BIC (MagRicfBicScorer).
class	LvHeuristic	This class represents the FCIT algorithm, which is an implementation of the FGES-FCI 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	RFCI.
class	SpFci	Adjusts GFCI to use a permutation algorithm (in this case SP) to do the initial steps of finding adjacencies and unshielded colliders.