2
* Licensed to the Apache Software Foundation (ASF) under one or more
3
* contributor license agreements. See the NOTICE file distributed with
4
* this work for additional information regarding copyright ownership.
5
* The ASF licenses this file to You under the Apache License, Version 2.0
6
* (the "License"); you may not use this file except in compliance with
7
* the License. You may obtain a copy of the License at
9
* http://www.apache.org/licenses/LICENSE-2.0
11
* Unless required by applicable law or agreed to in writing, software
12
* distributed under the License is distributed on an "AS IS" BASIS,
13
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14
* See the License for the specific language governing permissions and
15
* limitations under the License.
17
package org.apache.commons.math.stat.descriptive.moment;
19
import junit.framework.Test;
20
import junit.framework.TestSuite;
22
import org.apache.commons.math.stat.descriptive.StorelessUnivariateStatisticAbstractTest;
23
import org.apache.commons.math.stat.descriptive.UnivariateStatistic;
26
* Test cases for the {@link UnivariateStatistic} class.
28
* @version $Revision: 480442 $ $Date: 2006-11-29 00:21:22 -0700 (Wed, 29 Nov 2006) $
30
public class StandardDeviationTest extends StorelessUnivariateStatisticAbstractTest{
32
protected StandardDeviation stat;
37
public StandardDeviationTest(String name) {
42
* @see org.apache.commons.math.stat.descriptive.UnivariateStatisticAbstractTest#getUnivariateStatistic()
44
public UnivariateStatistic getUnivariateStatistic() {
45
return new StandardDeviation();
48
public static Test suite() {
49
TestSuite suite = new TestSuite(StandardDeviationTest.class);
50
suite.setName("StandardDeviation Tests");
55
* @see org.apache.commons.math.stat.descriptive.UnivariateStatisticAbstractTest#expectedValue()
57
public double expectedValue() {
62
* Make sure Double.NaN is returned iff n = 0
65
public void testNaN() {
66
StandardDeviation std = new StandardDeviation();
67
assertTrue(Double.isNaN(std.getResult()));
69
assertEquals(0d, std.getResult(), 0);
73
* Test population version of variance
75
public void testPopulation() {
76
double[] values = {-1.0d, 3.1d, 4.0d, -2.1d, 22d, 11.7d, 3d, 14d};
77
double sigma = populationStandardDeviation(values);
78
SecondMoment m = new SecondMoment();
79
m.evaluate(values); // side effect is to add values
80
StandardDeviation s1 = new StandardDeviation();
81
s1.setBiasCorrected(false);
82
assertEquals(sigma, s1.evaluate(values), 1E-14);
83
s1.incrementAll(values);
84
assertEquals(sigma, s1.getResult(), 1E-14);
85
s1 = new StandardDeviation(false, m);
86
assertEquals(sigma, s1.getResult(), 1E-14);
87
s1 = new StandardDeviation(false);
88
assertEquals(sigma, s1.evaluate(values), 1E-14);
89
s1.incrementAll(values);
90
assertEquals(sigma, s1.getResult(), 1E-14);
94
* Definitional formula for population standard deviation
96
protected double populationStandardDeviation(double[] v) {
97
double mean = new Mean().evaluate(v);
99
for (int i = 0; i < v.length; i++) {
100
sum += (v[i] - mean) * (v[i] - mean);
102
return Math.sqrt(sum / (double) v.length);