Class FractionDependentUnderAlternative
java.lang.Object
edu.cmu.tetrad.algcomparison.statistic.FractionDependentUnderAlternative
- All Implemented Interfaces:
- Statistic,- Serializable
Estimates whether the p-values under the null are Uniform usign the Markov Checker. This estimate the fraction of
 dependent judgements from the local Fraithfulness check, under the alternative hypothesis of dependence. This is only
 applicable to continuous data and really strictly only for Gaussian data.
- Version:
- $Id: $Id
- Author:
- josephramsey
- See Also:
- 
Constructor SummaryConstructorsConstructorDescriptionConstructor for FractionDependentUnderAlternative.FractionDependentUnderAlternative(double alpha) Constructor for FractionDependentUnderAlternative.
- 
Method SummaryModifier and TypeMethodDescriptionThe abbreviation for the statistic.Returns a short one-line description of this statistic.doublegetNormValue(double value) Returns a mapping of the statistic to the interval [0, 1], with higher being better.doublegetValue(Graph trueGraph, Graph estGraph, DataModel dataModel, Parameters parameters) Returns the value of this statistic, given the true graph and the estimated graph.voidsetAlpha(double alpha) Setter for the fieldalpha.
- 
Constructor Details- 
FractionDependentUnderAlternativepublic FractionDependentUnderAlternative()Constructor for FractionDependentUnderAlternative. 
- 
FractionDependentUnderAlternativepublic FractionDependentUnderAlternative(double alpha) Constructor for FractionDependentUnderAlternative. - Parameters:
- alpha- a double
 
 
- 
- 
Method Details- 
getAbbreviationThe abbreviation for the statistic. This will be printed at the top of each column.- Specified by:
- getAbbreviationin interface- Statistic
- Returns:
- This abbreviation.
 
- 
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:
- This description.
 
- 
getValueReturns the value of this statistic, given the true graph and the estimated graph.
- 
getNormValuepublic 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.- Specified by:
- getNormValuein interface- Statistic
- Parameters:
- value- The value of the statistic.
- Returns:
- The weight of the statistic, 0 to 1, higher is better.
 
- 
setAlphapublic void setAlpha(double alpha) Setter for the field alpha.- Parameters:
- alpha- a double
 
 
-