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Posted to commits@commons.apache.org by ah...@apache.org on 2021/12/17 21:46:18 UTC
[commons-statistics] 02/05: Update exponential distribution PDF
This is an automated email from the ASF dual-hosted git repository.
aherbert pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/commons-statistics.git
commit 670ad0a5119c21c203f46cbe90fe09bf6950a9cd
Author: Alex Herbert <ah...@apache.org>
AuthorDate: Fri Dec 17 00:50:14 2021 +0000
Update exponential distribution PDF
Directly implement the PDF using exp and do not use exp(logDensity(x)).
This is more accurate on extended precision test data.
Remove check that x >= +infinity in the log density. The result is the
same (-infinity) without this edge case check.
---
.../distribution/ExponentialDistribution.java | 11 +-
.../distribution/ExponentialDistributionTest.java | 14 +
.../commons/statistics/distribution/exppdf.csv | 3104 ++++++++++++++++++++
3 files changed, 3123 insertions(+), 6 deletions(-)
diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ExponentialDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ExponentialDistribution.java
index 93d51d2..123dba6 100644
--- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ExponentialDistribution.java
+++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ExponentialDistribution.java
@@ -70,17 +70,18 @@ public final class ExponentialDistribution extends AbstractContinuousDistributio
/** {@inheritDoc} */
@Override
public double density(double x) {
- return Math.exp(logDensity(x));
+ if (x < SUPPORT_LO) {
+ return 0;
+ }
+ return Math.exp(-x / mean) / mean;
}
/** {@inheritDoc} **/
@Override
public double logDensity(double x) {
- if (x < SUPPORT_LO ||
- x >= SUPPORT_HI) {
+ if (x < SUPPORT_LO) {
return Double.NEGATIVE_INFINITY;
}
-
return -x / mean - logMean;
}
@@ -99,7 +100,6 @@ public final class ExponentialDistribution extends AbstractContinuousDistributio
if (x <= SUPPORT_LO) {
return 0;
}
-
return -Math.expm1(-x / mean);
}
@@ -109,7 +109,6 @@ public final class ExponentialDistribution extends AbstractContinuousDistributio
if (x <= SUPPORT_LO) {
return 1;
}
-
return Math.exp(-x / mean);
}
diff --git a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/ExponentialDistributionTest.java b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/ExponentialDistributionTest.java
index 8726b8a..a9b8a7e 100644
--- a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/ExponentialDistributionTest.java
+++ b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/ExponentialDistributionTest.java
@@ -16,9 +16,12 @@
*/
package org.apache.commons.statistics.distribution;
+import java.math.BigDecimal;
import org.apache.commons.numbers.core.Precision;
import org.junit.jupiter.api.Assertions;
import org.junit.jupiter.api.Test;
+import org.junit.jupiter.params.ParameterizedTest;
+import org.junit.jupiter.params.provider.CsvFileSource;
/**
* Test cases for {@link ExponentialDistribution}.
@@ -76,4 +79,15 @@ class ExponentialDistributionTest extends BaseContinuousDistributionTest {
Assertions.assertEquals(0.0, d1.inverseCumulativeProbability(0.0));
Assertions.assertEquals(0.0, d1.inverseCumulativeProbability(-0.0));
}
+
+ @ParameterizedTest
+ @CsvFileSource(resources = "exppdf.csv")
+ void testPDF(double mean, double x, BigDecimal expected) {
+ final double e = expected.doubleValue();
+ final double a = ExponentialDistribution.of(mean).density(x);
+ // Require high precision.
+ // This has max error of 3 ulp if using exp(logDensity(x)).
+ Assertions.assertEquals(e, a, Math.ulp(e),
+ () -> "ULP error: " + expected.subtract(new BigDecimal(a)).doubleValue() / Math.ulp(e));
+ }
}
diff --git a/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/exppdf.csv b/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/exppdf.csv
new file mode 100644
index 0000000..2d88c22
--- /dev/null
+++ b/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/exppdf.csv
@@ -0,0 +1,3104 @@
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements. See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# High-precision test data for the exponential distribution PDF
+# Computed using the following maxima script:
+#
+# fpprec : 128;
+# f(mean, x) := bfloat(exp(-x / mean) / mean);
+# str(x) := ssubst("e","b",string(x));
+#
+# out : openw("exppdf.csv");
+# x : float(makelist(i / 128, i, 1, 128 * 12));
+# /* 2657 / 2^10 */
+# mean : 2.5947265625;
+# for i in x do printf(out, "~f, ~f, ~a~%", mean, i, str(f(mean, i))), fpprintprec : 30;
+# /* 1623468236L / 2^28 */
+# mean : 6.047890469431877;
+# for i in x do printf(out, "~f, ~f, ~a~%", mean, i, str(f(mean, i))), fpprintprec : 30;
+# close(out);
+
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