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Added support for Chi^2 analytic distribution to support degrees of freedom 0 (this will handle e.g. where a source had no independent dimensions)

This commit is contained in:
Joseph Lizier 2019-05-17 22:20:54 +10:00
parent fce1b34a5c
commit 8542d217ea
1 changed files with 22 additions and 2 deletions
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24
java/source/infodynamics/utils/ChiSquareMeasurementDistribution.java
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@ -97,8 +97,13 @@ public class ChiSquareMeasurementDistribution extends
super(0, 0);
this.numObservations = numObservations;
this.degreesOfFreedom = degreesOfFreedom;
chi2dist = new ChiSquaredDistribution(degreesOfFreedom); // Uncorrected distribution
meanOfUncorrectedDistribution = chi2dist.getNumericalMean() / (2.0*((double)numObservations));
if (degreesOfFreedom > 0) {
chi2dist = new ChiSquaredDistribution(degreesOfFreedom); // Uncorrected distribution
meanOfUncorrectedDistribution = chi2dist.getNumericalMean() / (2.0*((double)numObservations));
} else {
chi2dist = null; // Signal that all values will be (uncorrected) zero
meanOfUncorrectedDistribution = 0;
}
this.isBiasCorrected = isBiasCorrected;
this.actualValue = actualValue; // will be bias corrected, if we are bias correcting
// Now we can properly compute the p-value of this potentially bias corrected actual value
@ -106,6 +111,14 @@ public class ChiSquareMeasurementDistribution extends
}
public double computePValueForGivenEstimate(double estimate) {
if (chi2dist == null) {
if (estimate > 0) {
return 1;
} else {
return 0;
}
}
// Postcondition: we have a valid chi2dist:
if (isBiasCorrected) {
// estimate is biasCorrected, so we need to add back into it the meanOfUncorrectedDistribution
return 1 - MathsUtils.chiSquareCdf(2.0*((double)numObservations)*(estimate + meanOfUncorrectedDistribution), degreesOfFreedom);
@ -115,6 +128,10 @@ public class ChiSquareMeasurementDistribution extends
}
public double computeEstimateForGivenPValue(double pValue) {
if (chi2dist == null) {
// All p-values map to estimate 0
return 0;
}
double uncorrectedEstimate = chi2dist.inverseCumulativeProbability(1 - pValue) / (2.0*((double)numObservations));
if (isBiasCorrected) {
return uncorrectedEstimate - meanOfUncorrectedDistribution;
@ -152,6 +169,9 @@ public class ChiSquareMeasurementDistribution extends
* @return the standard deviation
*/
public double getStdOfDistribution() {
if (chi2dist == null) {
return 0; // All nulls are 0
}
return Math.sqrt(chi2dist.getNumericalVariance()) / (2.0*((double)numObservations));
}
}