Uses of Annotation Interface
edu.cmu.tetrad.annotation.Experimental
Packages that use Experimental
Package
Description
A package for algorithms that are not ready for prime time.
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Uses of Experimental in edu.cmu.tetrad.algcomparison.algorithm.multi
Classes in edu.cmu.tetrad.algcomparison.algorithm.multi with annotations of type ExperimentalModifier and TypeClassDescriptionclassWraps the MultiFask algorithm for continuous variables. -
Uses of Experimental in edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag
Classes in edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag with annotations of type ExperimentalModifier and TypeClassDescriptionclassRepresents the CAM algorithm, which is a causal additive model search algorithm.classCD-NOD wrapper for algcomparison.classGIN (Generalized Independent Noise Search)classIS-FGES (Instance-Specific FGES) wrapper for the algcomparison interface.classPCMCI wrapper for algcomparison.classSP (Sparsest Permutation) -
Uses of Experimental in edu.cmu.tetrad.algcomparison.algorithm.oracle.pag
Classes in edu.cmu.tetrad.algcomparison.algorithm.oracle.pag with annotations of type ExperimentalModifier and TypeClassDescriptionclassThis 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.classThis class represents the Detect-Mimic-FCIT (DM-FCIT) algorithm, a specialized variant of the DM-PC and FCIT algorithms designed to identify intermediate latent variables.classFCI-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).classThis 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.classIS-GFCI (Instance-Specific GFCI) wrapper for the algcomparison interface.classRuns RFCI-BSC, which is RFCI with bootstrap sampling of PAGs. -
Uses of Experimental in edu.cmu.tetrad.algcomparison.algorithm.other
Classes in edu.cmu.tetrad.algcomparison.algorithm.other with annotations of type Experimental -
Uses of Experimental in edu.cmu.tetrad.algcomparison.independence
Classes in edu.cmu.tetrad.algcomparison.independence with annotations of type Experimental -
Uses of Experimental in edu.cmu.tetrad.algcomparison.score
Classes in edu.cmu.tetrad.algcomparison.score with annotations of type Experimental -
Uses of Experimental in edu.cmu.tetrad.algcomparison.simulation
Classes in edu.cmu.tetrad.algcomparison.simulation with annotations of type ExperimentalModifier and TypeClassDescriptionclassA simulation method based on the mixed variable polynomial assumption. -
Uses of Experimental in edu.cmu.tetrad.data.simulation
Classes in edu.cmu.tetrad.data.simulation with annotations of type ExperimentalModifier and TypeClassDescriptionclassLoad data sets and graphs from a directory.classLoad data sets and graphs from a directory. -
Uses of Experimental in edu.cmu.tetrad.search.work_in_progress
Classes in edu.cmu.tetrad.search.work_in_progress with annotations of type ExperimentalModifier and TypeClassDescriptionclassGives a BIC score for a linear, Gaussian MAG (Mixed Ancestral Graph).classGives a BIC score for a linear, Gaussian MAG (Mixed Ancestral Graph).classGives a BIC score for a linear, Gaussian MAG (Mixed Ancestral Graph).