Class FractionDependentUnderNull
java.lang.Object
edu.cmu.tetrad.algcomparison.statistic.FractionDependentUnderNull
- 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:
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Constructor Summary
ConstructorsConstructorDescriptionConstructor for FractionDependentUnderNull.FractionDependentUnderNull
(double alpha) Constructor for FractionDependentUnderNull. -
Method Summary
Modifier and TypeMethodDescriptionThe abbreviation for the statistic.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
Returns the value of this statistic, given the true graph and the estimated graph.void
setAlpha
(double alpha) Setter for the fieldalpha
.
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Constructor Details
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FractionDependentUnderNull
public FractionDependentUnderNull()Constructor for FractionDependentUnderNull.
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FractionDependentUnderNull
public FractionDependentUnderNull(double alpha) Constructor for FractionDependentUnderNull.
- Parameters:
alpha
- a double
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Method Details
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getAbbreviation
The abbreviation for the statistic. This will be printed at the top of each column.- Specified by:
getAbbreviation
in interfaceStatistic
- Returns:
- This abbreviation.
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getDescription
Returns a short one-line description of this statistic. This will be printed at the beginning of the report.- Specified by:
getDescription
in interfaceStatistic
- Returns:
- This description.
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getValue
Returns the value of this statistic, given the true graph and the estimated graph. -
getNormValue
public 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:
getNormValue
in interfaceStatistic
- Parameters:
value
- The value of the statistic.- Returns:
- The weight of the statistic, 0 to 1, higher is better.
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setAlpha
public void setAlpha(double alpha) Setter for the field
alpha
.- Parameters:
alpha
- a double
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