Class TrueDagFalsePositiveArrow
java.lang.Object
edu.cmu.tetrad.algcomparison.statistic.TrueDagFalsePositiveArrow
- All Implemented Interfaces:
- Statistic,- Serializable
Represents a statistic that calculates the false positives for arrows compared to the true directed acyclic graph
 (DAG).
- See Also:
- 
Constructor SummaryConstructorsConstructorDescriptionThis class represents a statistic that calculates the false positives for arrows compared to the true DAG.
- 
Method SummaryModifier and TypeMethodDescriptionRetrieves the abbreviation for the statistic.Returns a short one-line description of this statistic.doublegetNormValue(double value) Retrieves the normalized value of the statistic.doublegetValue(Graph trueGraph, Graph estGraph, DataModel dataModel, Parameters parameters) Calculates the false positives for arrows compared to the true DAG.
- 
Constructor Details- 
TrueDagFalsePositiveArrowpublic TrueDagFalsePositiveArrow()This class represents a statistic that calculates the false positives for arrows compared to the true DAG.
 
- 
- 
Method Details- 
getAbbreviationRetrieves the abbreviation for the statistic.- Specified by:
- getAbbreviationin interface- Statistic
- Returns:
- The abbreviation for the statistic.
 
- 
getDescriptionReturns a short one-line description of this statistic. This will be printed at the beginning of the report.- Specified by:
- getDescriptionin interface- Statistic
- Returns:
- The description of this statistic.
 
- 
getValueCalculates the false positives for arrows compared to the true DAG.- Specified by:
- getValuein interface- Statistic
- Parameters:
- trueGraph- The true graph (DAG, CPDAG, PAG_of_the_true_DAG).
- estGraph- The estimated graph (same type).
- dataModel- The data model.
- parameters- The parameters.
- Returns:
- The number of false positive arrows in the estimated graph compared to the true graph.
 
- 
getNormValuepublic double getNormValue(double value) Retrieves the normalized value of the statistic.- Specified by:
- getNormValuein interface- Statistic
- Parameters:
- value- The value of the statistic.
- Returns:
- The normalized value of the statistic, between 0 and 1, inclusive.
 
 
-