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In LogNormalDistribution and LogNormalDistributionTest 

- "mean" (of the underlying normal distribution) is now called "scale"
  - "standard deviation" (of the underlying normal distribution) is now called "shape"
  - in the javadoc, removed html links that point to internal anchors.

git-svn-id: https://svn.apache.org/repos/asf/commons/proper/math/trunk@1232755 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Sebastien Brisard 2012-01-18 06:17:05 +00:00
parent e2c0e16bff
commit 47a87ce229
2 changed files with 13 additions and 16 deletions
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20
src/main/java/org/apache/commons/math/distribution/LogNormalDistribution.java
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@ -27,7 +27,7 @@ import org.apache.commons.math.util.FastMath;
* Implementation of the log-normal (gaussian) distribution. * Implementation of the log-normal (gaussian) distribution.
* *
* <p> * <p>
* <a id="parameters"><strong>Parameters:</strong></a> * <strong>Parameters:</strong>
* {@code X} is log-normally distributed if its natural logarithm {@code log(X)} * {@code X} is log-normally distributed if its natural logarithm {@code log(X)}
* is normally distributed. The probability distribution function of {@code X} * is normally distributed. The probability distribution function of {@code X}
* is given by (for {@code x > 0}) * is given by (for {@code x > 0})
@ -64,19 +64,17 @@ public class LogNormalDistribution extends AbstractRealDistribution {
/** &radic;(2) */ /** &radic;(2) */
private static final double SQRT2 = FastMath.sqrt(2.0); private static final double SQRT2 = FastMath.sqrt(2.0);
/** The <a href="#parameters">scale</a> parameter of this distribution. */ /** The scale parameter of this distribution. */
private final double scale; private final double scale;
/** The <a href="#parameters">shape</a> parameter of this distribution. */ /** The shape parameter of this distribution. */
private final double shape; private final double shape;
/** Inverse cumulative probability accuracy. */ /** Inverse cumulative probability accuracy. */
private final double solverAbsoluteAccuracy; private final double solverAbsoluteAccuracy;
/** /**
* Create a log-normal distribution using the specified * Create a log-normal distribution using the specified scale and shape.
* <a href="#parameters">scale</a> and
* <a href="#parameters">shape</a>.
* *
* @param scale the scale parameter of this distribution * @param scale the scale parameter of this distribution
* @param shape the shape parameter of this distribution * @param shape the shape parameter of this distribution
@ -88,8 +86,7 @@ public class LogNormalDistribution extends AbstractRealDistribution {
} }
/** /**
* Create a log-normal distribution using the specified * Create a log-normal distribution using the specified scale, shape and
* <a href="#parameters">scale</a>, <a href="#parameters">shape</a> and
* inverse cumulative distribution accuracy. * inverse cumulative distribution accuracy.
* *
* @param scale the scale parameter of this distribution * @param scale the scale parameter of this distribution
@ -100,7 +97,7 @@ public class LogNormalDistribution extends AbstractRealDistribution {
public LogNormalDistribution(double scale, double shape, public LogNormalDistribution(double scale, double shape,
double inverseCumAccuracy) throws NotStrictlyPositiveException { double inverseCumAccuracy) throws NotStrictlyPositiveException {
if (shape <= 0) { if (shape <= 0) {
throw new NotStrictlyPositiveException(LocalizedFormats.STANDARD_DEVIATION, shape); throw new NotStrictlyPositiveException(LocalizedFormats.SHAPE, shape);
} }
this.scale = scale; this.scale = scale;
@ -120,7 +117,7 @@ public class LogNormalDistribution extends AbstractRealDistribution {
} }
/** /**
* Returns the <a href="#parameters">scale</a> parameter of this distribution. * Returns the scale parameter of this distribution.
* *
* @return the scale parameter * @return the scale parameter
*/ */
@ -129,8 +126,7 @@ public class LogNormalDistribution extends AbstractRealDistribution {
} }
/** /**
* Returns the <a href="#parameters">shape</a> parameter of this * Returns the shape parameter of this distribution.
* distribution.
* *
* @return the shape parameter * @return the shape parameter
*/ */

9
src/test/java/org/apache/commons/math/distribution/LogNormalDistributionTest.java
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@ -164,13 +164,13 @@ public class LogNormalDistributionTest extends RealDistributionAbstractTest {
} }
@Test @Test
public void testGetMean() { public void testGetScale() {
LogNormalDistribution distribution = (LogNormalDistribution)getDistribution(); LogNormalDistribution distribution = (LogNormalDistribution)getDistribution();
Assert.assertEquals(2.1, distribution.getScale(), 0); Assert.assertEquals(2.1, distribution.getScale(), 0);
} }
@Test @Test
public void testGetStandardDeviation() { public void testGetShape() {
LogNormalDistribution distribution = (LogNormalDistribution)getDistribution(); LogNormalDistribution distribution = (LogNormalDistribution)getDistribution();
Assert.assertEquals(1.4, distribution.getShape(), 0); Assert.assertEquals(1.4, distribution.getShape(), 0);
} }
@ -193,8 +193,9 @@ public class LogNormalDistributionTest extends RealDistributionAbstractTest {
0.1836267118}); 0.1836267118});
} }
private void checkDensity(double mean, double sd, double[] x, double[] expected) { private void checkDensity(double scale, double shape, double[] x,
LogNormalDistribution d = new LogNormalDistribution(mean, sd); double[] expected) {
LogNormalDistribution d = new LogNormalDistribution(scale, shape);
for (int i = 0; i < x.length; i++) { for (int i = 0; i < x.length; i++) {
Assert.assertEquals(expected[i], d.density(x[i]), 1e-9); Assert.assertEquals(expected[i], d.density(x[i]), 1e-9);
} }