Package edu.cmu.tetrad.algcomparison.statistic

Interface Statistic

All Superinterfaces:

Serializable

All Known Implementing Classes:

AdjacencyFn, AdjacencyFp, AdjacencyFpr, AdjacencyPrecision, AdjacencyRecall, AdjacencyTn, AdjacencyTp, AdjacencyTpr, AncestorF1, AncestorPrecision, AncestorRecall, AncestralPrecision, AncestralRecall, ArrowheadFn, ArrowheadFp, ArrowheadFpr, ArrowheadPrecision, ArrowheadPrecisionCommonEdges, ArrowheadRecall, ArrowheadRecallCommonEdges, ArrowheadTn, ArrowheadTp, AverageDegreeEst, AverageDegreeTrue, BicDiff, BicDiffPerRecord, BicEst, BicTrue, BidirectedEst, BidirectedFP, BidirectedLatentPrecision, BidirectedPrecision, BidirectedRecall, BidirectedTP, BidirectedTrue, CommonAncestorFalseNegativeBidirected, CommonAncestorFalsePositiveBidirected, CommonAncestorTruePositiveBidirected, CommonMeasuredAncestorRecallBidirected, CorrectSkeleton, DefiniteDirectedPathPrecision, DefiniteDirectedPathRecall, DensityEst, DensityTrue, ElapsedCpuTime, F1Adj, F1All, F1Arrow, FalseNegativesAdjacencies, FalsePositiveAdjacencies, FBetaAdj, FractionDependentUnderAlternative, FractionDependentUnderNull, GraphExactlyRight, IdaAverageSquaredDistance, IdaCheckAvgMaxSquaredDiffEstTrue, IdaCheckAvgMinSquaredDiffEstTrue, IdaCheckAvgSquaredDifference, IdaMaximumSquaredDifference, IdaMinimumSquaredDifference, ImpliedArrowOrientationRatioEst, ImpliedArrowOrientationRatioEst2, ImpliedOrientationRatioEst, ImpliesLegalMag, KnowledgeSatisfied, LatentCommonAncestorFalseNegativeBidirected, LatentCommonAncestorFalsePositiveBidirected, LatentCommonAncestorRecallBidirected, LatentCommonAncestorTruePositiveBidirected, LegalPag, LocalGraphPrecision, LocalGraphRecall, MagCgScore, MagDgScore, MagSemScore, MarkovCheckAdPasses, MarkovCheckAdPassesBestOf10, MarkovCheckAndersonDarlingP, MarkovCheckAndersonDarlingPBestOf10, MarkovCheckBinomialP, MarkovCheckBinomialPBestOf10, MarkovCheckKolmogorovSmirnoffP, MarkovCheckKolmogorovSmirnoffPBestOf10, MarkovCheckKsPasses, MarkovCheckKsPassesBestOf10, MathewsCorrAdj, MathewsCorrArrow, Maximal, MaximalityCondition, NoAlmostCyclicPathsCondition, NoCyclicPathsCondition, NodesInCyclesPrecision, NodesInCyclesRecall, NonancestorPrecision, NonancestorRecall, NoSemidirectedF1, NoSemidirectedPrecision, NoSemidirectedRecall, NumAmbiguousTriples, NumberArrowsEst, NumberArrowsNotInUnshieldedCollidersEst, NumberCollidersEst, NumberEdgesEst, NumberEdgesInCollidersEst, NumberEdgesInUnshieldedCollidersEst, NumberEdgesTrue, NumberOfEdgesEst, NumberOfEdgesTrue, NumberTailsEst, NumberUnshieldedCollidersEst, NumBidirectedBothNonancestorAncestor, NumBidirectedEdgesEst, NumBidirectedEdgesTrue, NumColoredDD, NumColoredNL, NumColoredPD, NumColoredPL, NumCommonMeasuredAncestorBidirected, NumCompatibleDefiniteDirectedEdgeAncestors, NumCompatibleDirectedEdgeConfounded, NumCompatibleDirectedEdgeNonAncestors, NumCompatibleEdges, NumCompatiblePossiblyDirectedEdgeAncestors, NumCompatiblePossiblyDirectedEdgeNonAncestors, NumCompatibleVisibleNonancestors, NumCorrectBidirected, NumCorrectDDAncestors, NumCorrectPDAncestors, NumCorrectVisibleEdges, NumCoveringAdjacenciesInPag, NumDefinitelyDirected, NumDefinitelyNotDirectedPaths, NumDirectedEdgeAncestors, NumDirectedEdgeBnaMeasuredCounfounded, NumDirectedEdgeNoMeasureAncestors, NumDirectedEdgeNotAncNotRev, NumDirectedEdgeReversed, NumDirectedEdges, NumDirectedPathsEst, NumDirectedPathsTrue, NumDirectedShouldBePartiallyDirected, NumEdgeInEstInTrue, NumGenuineAdjacenciesInPag, NumIncorrectDDAncestors, NumIncorrectPDAncestors, NumIncorrectVisibleAncestors, NumLatentCommonAncestorBidirected, NumNondirectedEdges, NumParametersEst, NumPartiallyOrientedEdges, NumPossiblyDirected, NumUndirectedEdges, NumVisibleEdgeEst, NumVisibleEdges, NumVisibleEdgeTrue, OrientationPrecision, OrientationRecall, PagAdjacencyPrecision, PagAdjacencyRecall, ParameterColumn, PercentAmbiguous, PercentBidirectedEdges, ProportionSemidirectedPathsNotReversedEst, ProportionSemidirectedPathsNotReversedTrue, PvalueDistanceToAlpha, PvalueUniformityUnderNull, SemidirectedPathF1, SemidirectedPrecision, SemidirectedRecall, StructuralHammingDistance, TailPrecision, TailRecall, TrueDagFalseNegativesArrows, TrueDagFalseNegativesTails, TrueDagFalsePositiveArrow, TrueDagFalsePositiveTails, TrueDagPrecisionArrow, TrueDagPrecisionTails, TrueDagRecallArrows, TrueDagRecallTails, TrueDagTruePositiveArrow, TrueDagTruePositiveDirectedPathNonancestor, TrueDagTruePositiveTails, TwoCycleFalseNegative, TwoCycleFalsePositive, TwoCyclePrecision, TwoCycleRecall, TwoCycleTruePositive

public interface Statistic
extends Serializable

The interface that each statistic needs to implement.

Version:

$Id: $Id

Author:

josephramsey

Field Summary

Fields

Modifier and Type	Field	Description
static final long	serialVersionUID	Constant serialVersionUID=23L

Method Summary

Modifier and Type	Method	Description
String	getAbbreviation()	The abbreviation for the statistic.
String	getDescription()	Returns a short one-line description of this statistic.
double	getNormValue(double value)	Returns a mapping of the statistic to the interval [0, 1], with higher being better.
double	getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.

Field Details

serialVersionUID

static final long serialVersionUID

Constant serialVersionUID=23L

See Also:

• Constant Field Values

Method Details

getAbbreviation

String getAbbreviation()

The abbreviation for the statistic. This will be printed at the top of each column.

Returns:

This abbreviation.

getDescription

String getDescription()

Returns a short one-line description of this statistic. This will be printed at the beginning of the report.

Returns:

This description.

getValue

double getValue(Graph trueGraph,
 Graph estGraph,
 DataModel dataModel)

Returns the value of this statistic, given the true graph and the estimated graph.

Parameters:

trueGraph - The true graph (DAG, CPDAG, PAG_of_the_true_DAG).

estGraph - The estimated graph (same type).

dataModel - The data model.

Returns:

The value of the statistic.

getNormValue

double getNormValue(double value)

Returns a mapping of the statistic to the interval [0, 1], with higher being better. This is used for a calculation of a utility for an algorithm. If the statistic is already between 0 and 1, you can just return the statistic.

Parameters:

value - The value of the statistic.

Returns:

The weight of the statistic, 0 to 1, higher is better.