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Removed dependency on DistributionFactory. Added settable t distribution field. 

git-svn-id: https://svn.apache.org/repos/asf/jakarta/commons/proper/math/trunk@545169 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Brent Worden 2007-06-07 13:22:45 +00:00
parent 8d14277eb6
commit 879a6c0e07
1 changed files with 34 additions and 19 deletions
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51
src/java/org/apache/commons/math/stat/inference/TTestImpl.java
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@ -19,6 +19,7 @@ package org.apache.commons.math.stat.inference;
import org.apache.commons.math.MathException; import org.apache.commons.math.MathException;
import org.apache.commons.math.distribution.DistributionFactory; import org.apache.commons.math.distribution.DistributionFactory;
import org.apache.commons.math.distribution.TDistribution; import org.apache.commons.math.distribution.TDistribution;
import org.apache.commons.math.distribution.TDistributionImpl;
import org.apache.commons.math.stat.StatUtils; import org.apache.commons.math.stat.StatUtils;
import org.apache.commons.math.stat.descriptive.StatisticalSummary; import org.apache.commons.math.stat.descriptive.StatisticalSummary;
@ -32,14 +33,25 @@ import org.apache.commons.math.stat.descriptive.StatisticalSummary;
*/ */
public class TTestImpl implements TTest { public class TTestImpl implements TTest {
/** Cached DistributionFactory used to create TDistribution instances */ /** Distribution used to compute inference statistics. */
private DistributionFactory distributionFactory = null; private TDistribution distribution;
/** /**
* Default constructor. * Default constructor.
*/ */
public TTestImpl() { public TTestImpl() {
this(new TDistributionImpl(1.0));
}
/**
* Create a test instance using the given distribution for computing
* inference statistics.
* @param t distribution used to compute inference statistics.
* @since 1.2
*/
public TTestImpl(TDistribution t) {
super(); super();
setDistribution(t);
} }
/** /**
@ -910,12 +922,10 @@ public class TTestImpl implements TTest {
/** /**
* Gets a DistributionFactory to use in creating TDistribution instances. * Gets a DistributionFactory to use in creating TDistribution instances.
* @return a distribution factory. * @return a distribution factory.
* @deprecated inject TDistribution directly instead of using a factory.
*/ */
protected DistributionFactory getDistributionFactory() { protected DistributionFactory getDistributionFactory() {
if (distributionFactory == null) { return DistributionFactory.newInstance();
distributionFactory = DistributionFactory.newInstance();
}
return distributionFactory;
} }
/** /**
@ -995,9 +1005,8 @@ public class TTestImpl implements TTest {
protected double tTest(double m, double mu, double v, double n) protected double tTest(double m, double mu, double v, double n)
throws MathException { throws MathException {
double t = Math.abs(t(m, mu, v, n)); double t = Math.abs(t(m, mu, v, n));
TDistribution tDistribution = distribution.setDegreesOfFreedom(n - 1);
getDistributionFactory().createTDistribution(n - 1); return 1.0 - distribution.cumulativeProbability(-t, t);
return 1.0 - tDistribution.cumulativeProbability(-t, t);
} }
/** /**
@ -1020,10 +1029,9 @@ public class TTestImpl implements TTest {
throws MathException { throws MathException {
double t = Math.abs(t(m1, m2, v1, v2, n1, n2)); double t = Math.abs(t(m1, m2, v1, v2, n1, n2));
double degreesOfFreedom = 0; double degreesOfFreedom = 0;
degreesOfFreedom= df(v1, v2, n1, n2); degreesOfFreedom = df(v1, v2, n1, n2);
TDistribution tDistribution = distribution.setDegreesOfFreedom(degreesOfFreedom);
getDistributionFactory().createTDistribution(degreesOfFreedom); return 1.0 - distribution.cumulativeProbability(-t, t);
return 1.0 - tDistribution.cumulativeProbability(-t, t);
} }
/** /**
@ -1045,10 +1053,17 @@ public class TTestImpl implements TTest {
double v2, double n1, double n2) double v2, double n1, double n2)
throws MathException { throws MathException {
double t = Math.abs(homoscedasticT(m1, m2, v1, v2, n1, n2)); double t = Math.abs(homoscedasticT(m1, m2, v1, v2, n1, n2));
double degreesOfFreedom = 0; double degreesOfFreedom = (double) (n1 + n2 - 2);
degreesOfFreedom = (double) (n1 + n2 - 2); distribution.setDegreesOfFreedom(degreesOfFreedom);
TDistribution tDistribution = return 1.0 - distribution.cumulativeProbability(-t, t);
getDistributionFactory().createTDistribution(degreesOfFreedom); }
return 1.0 - tDistribution.cumulativeProbability(-t, t);
/**
* Modify the distribution used to compute inference statistics.
* @param value the new distribution
* @since 1.2
*/
public void setDistribution(TDistribution value) {
distribution = value;
} }
} }