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.
- Author:
- josephramsey
- See Also:
-
Constructor Summary
Constructors -
Method Summary
Modifier 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.doubleReturns the value of this statistic, given the true graph and the estimated graph.voidsetAlpha(double alpha)
-
Constructor Details
-
FractionDependentUnderAlternative
public FractionDependentUnderAlternative() -
FractionDependentUnderAlternative
public FractionDependentUnderAlternative(double alpha)
-
-
Method Details
-
getAbbreviation
Description copied from interface:StatisticThe abbreviation for the statistic. This will be printed at the top of each column.- Specified by:
getAbbreviationin interfaceStatistic- Returns:
- Thsi abbreviation.
-
getDescription
Description copied from interface:StatisticReturns a short one-line description of this statistic. This will be printed at the beginning of the report.- Specified by:
getDescriptionin interfaceStatistic- Returns:
- This description.
-
getValue
Description copied from interface:StatisticReturns the value of this statistic, given the true graph and the estimated graph. -
getNormValue
public double getNormValue(double value) Description copied from interface:StatisticReturns 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 interfaceStatistic- Parameters:
value- The value of the statistic.- Returns:
- The weight of the statistic, 0 to 1, higher is better.
-
setAlpha
public void setAlpha(double alpha)
-