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

Packages that use TakesCovarianceMatrix
  • Uses of TakesCovarianceMatrix in edu.cmu.tetrad.algcomparison.algorithm.cluster

    Modifier and Type
    Class
    Description
    class 
    Build Pure Clusters.
    class 
    Find One Factor Clusters.
    class 
    FTFC.
  • Uses of TakesCovarianceMatrix in edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag

    Modifier and Type
    Class
    Description
    class 
    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

    Modifier and Type
    Class
    Description
    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 
    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.