KickJava   Java API By Example, From Geeks To Geeks.

Java > Open Source Codes > org > apache > commons > math > stat > regression > SimpleRegressionTest


1 /*
2  * Copyright 2003-2004 The Apache Software Foundation.
3  *
4  * Licensed under the Apache License, Version 2.0 (the "License");
5  * you may not use this file except in compliance with the License.
6  * You may obtain a copy of the License at
7  *
8  * http://www.apache.org/licenses/LICENSE-2.0
9  *
10  * Unless required by applicable law or agreed to in writing, software
11  * distributed under the License is distributed on an "AS IS" BASIS,
12  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13  * See the License for the specific language governing permissions and
14  * limitations under the License.
15  */
16 package org.apache.commons.math.stat.regression;
17
18 import java.util.Random JavaDoc;
19
20 import junit.framework.Test;
21 import junit.framework.TestCase;
22 import junit.framework.TestSuite;
23 /**
24  * Test cases for the TestStatistic class.
25  *
26  * @version $Revision$ $Date: 2005-02-26 05:11:52 -0800 (Sat, 26 Feb 2005) $
27  */
28
29 public final class SimpleRegressionTest extends TestCase {
30
31     /*
32      * NIST "Norris" refernce data set from
33      * http://www.itl.nist.gov/div898/strd/lls/data/LINKS/DATA/Norris.dat
34      * Strangely, order is {y,x}
35      */
36     private double[][] data = { { 0.1, 0.2 }, {338.8, 337.4 }, {118.1, 118.2 },
37             {888.0, 884.6 }, {9.2, 10.1 }, {228.1, 226.5 }, {668.5, 666.3 }, {998.5, 996.3 },
38             {449.1, 448.6 }, {778.9, 777.0 }, {559.2, 558.2 }, {0.3, 0.4 }, {0.1, 0.6 }, {778.1, 775.5 },
39             {668.8, 666.9 }, {339.3, 338.0 }, {448.9, 447.5 }, {10.8, 11.6 }, {557.7, 556.0 },
40             {228.3, 228.1 }, {998.0, 995.8 }, {888.8, 887.6 }, {119.6, 120.2 }, {0.3, 0.3 },
41             {0.6, 0.3 }, {557.6, 556.8 }, {339.3, 339.1 }, {888.0, 887.2 }, {998.5, 999.0 },
42             {778.9, 779.0 }, {10.2, 11.1 }, {117.6, 118.3 }, {228.9, 229.2 }, {668.4, 669.1 },
43             {449.2, 448.9 }, {0.2, 0.5 }
44     };
45
46     /*
47      * Correlation example from
48      * http://www.xycoon.com/correlation.htm
49      */
50     private double[][] corrData = { { 101.0, 99.2 }, {100.1, 99.0 }, {100.0, 100.0 },
51             {90.6, 111.6 }, {86.5, 122.2 }, {89.7, 117.6 }, {90.6, 121.1 }, {82.8, 136.0 },
52             {70.1, 154.2 }, {65.4, 153.6 }, {61.3, 158.5 }, {62.5, 140.6 }, {63.6, 136.2 },
53             {52.6, 168.0 }, {59.7, 154.3 }, {59.5, 149.0 }, {61.3, 165.5 }
54     };
55
56     /*
57      * From Moore and Mcabe, "Introduction to the Practice of Statistics"
58      * Example 10.3
59      */
60     private double[][] infData = { { 15.6, 5.2 }, {26.8, 6.1 }, {37.8, 8.7 }, {36.4, 8.5 },
61             {35.5, 8.8 }, {18.6, 4.9 }, {15.3, 4.5 }, {7.9, 2.5 }, {0.0, 1.1 }
62     };
63     
64     /*
65      * Data with bad linear fit
66      */
67     private double[][] infData2 = { { 1, 1 }, {2, 0 }, {3, 5 }, {4, 2 },
68             {5, -1 }, {6, 12 }
69     };
70
71     public SimpleRegressionTest(String JavaDoc name) {
72         super(name);
73     }
74
75     public void setUp() {
76     }
77
78     public static Test suite() {
79         TestSuite suite = new TestSuite(SimpleRegressionTest.class);
80         suite.setName("BivariateRegression Tests");
81         return suite;
82     }
83
84     public void testNorris() {
85         SimpleRegression regression = new SimpleRegression();
86         for (int i = 0; i < data.length; i++) {
87             regression.addData(data[i][1], data[i][0]);
88         }
89         // Tests against certified values from
90 // http://www.itl.nist.gov/div898/strd/lls/data/LINKS/DATA/Norris.dat
91 assertEquals("slope", 1.00211681802045, regression.getSlope(), 10E-12);
92         assertEquals("slope std err", 0.429796848199937E-03,
93                 regression.getSlopeStdErr(),10E-12);
94         assertEquals("number of observations", 36, regression.getN());
95         assertEquals( "intercept", -0.262323073774029,
96             regression.getIntercept(),10E-12);
97         assertEquals("std err intercept", 0.232818234301152,
98             regression.getInterceptStdErr(),10E-12);
99         assertEquals("r-square", 0.999993745883712,
100             regression.getRSquare(), 10E-12);
101         assertEquals("SSR", 4255954.13232369,
102             regression.getRegressionSumSquares(), 10E-9);
103         assertEquals("MSE", 0.782864662630069,
104             regression.getMeanSquareError(), 10E-10);
105         assertEquals("SSE", 26.6173985294224,
106             regression.getSumSquaredErrors(),10E-9);
107         // ------------ End certified data tests
108
109         assertEquals( "predict(0)", -0.262323073774029,
110             regression.predict(0), 10E-12);
111         assertEquals("predict(1)", 1.00211681802045 - 0.262323073774029,
112             regression.predict(1), 10E-12);
113     }
114
115     public void testCorr() {
116         SimpleRegression regression = new SimpleRegression();
117         regression.addData(corrData);
118         assertEquals("number of observations", 17, regression.getN());
119         assertEquals("r-square", .896123, regression.getRSquare(), 10E-6);
120         assertEquals("r", -0.94663767742, regression.getR(), 1E-10);
121     }
122
123     public void testNaNs() {
124         SimpleRegression regression = new SimpleRegression();
125         assertTrue("intercept not NaN", Double.isNaN(regression.getIntercept()));
126         assertTrue("slope not NaN", Double.isNaN(regression.getSlope()));
127         assertTrue("slope std err not NaN", Double.isNaN(regression.getSlopeStdErr()));
128         assertTrue("intercept std err not NaN", Double.isNaN(regression.getInterceptStdErr()));
129         assertTrue("MSE not NaN", Double.isNaN(regression.getMeanSquareError()));
130         assertTrue("e not NaN", Double.isNaN(regression.getR()));
131         assertTrue("r-square not NaN", Double.isNaN(regression.getRSquare()));
132         assertTrue( "RSS not NaN", Double.isNaN(regression.getRegressionSumSquares()));
133         assertTrue("SSE not NaN",Double.isNaN(regression.getSumSquaredErrors()));
134         assertTrue("SSTO not NaN", Double.isNaN(regression.getTotalSumSquares()));
135         assertTrue("predict not NaN", Double.isNaN(regression.predict(0)));
136
137         regression.addData(1, 2);
138         regression.addData(1, 3);
139
140         // No x variation, so these should still blow...
141 assertTrue("intercept not NaN", Double.isNaN(regression.getIntercept()));
142         assertTrue("slope not NaN", Double.isNaN(regression.getSlope()));
143         assertTrue("slope std err not NaN", Double.isNaN(regression.getSlopeStdErr()));
144         assertTrue("intercept std err not NaN", Double.isNaN(regression.getInterceptStdErr()));
145         assertTrue("MSE not NaN", Double.isNaN(regression.getMeanSquareError()));
146         assertTrue("e not NaN", Double.isNaN(regression.getR()));
147         assertTrue("r-square not NaN", Double.isNaN(regression.getRSquare()));
148         assertTrue("RSS not NaN", Double.isNaN(regression.getRegressionSumSquares()));
149         assertTrue("SSE not NaN", Double.isNaN(regression.getSumSquaredErrors()));
150         assertTrue("predict not NaN", Double.isNaN(regression.predict(0)));
151
152         // but SSTO should be OK
153 assertTrue("SSTO NaN", !Double.isNaN(regression.getTotalSumSquares()));
154
155         regression = new SimpleRegression();
156
157         regression.addData(1, 2);
158         regression.addData(3, 3);
159
160         // All should be OK except MSE, s(b0), s(b1) which need one more df
161 assertTrue("interceptNaN", !Double.isNaN(regression.getIntercept()));
162         assertTrue("slope NaN", !Double.isNaN(regression.getSlope()));
163         assertTrue ("slope std err not NaN", Double.isNaN(regression.getSlopeStdErr()));
164         assertTrue("intercept std err not NaN", Double.isNaN(regression.getInterceptStdErr()));
165         assertTrue("MSE not NaN", Double.isNaN(regression.getMeanSquareError()));
166         assertTrue("r NaN", !Double.isNaN(regression.getR()));
167         assertTrue("r-square NaN", !Double.isNaN(regression.getRSquare()));
168         assertTrue("RSS NaN", !Double.isNaN(regression.getRegressionSumSquares()));
169         assertTrue("SSE NaN", !Double.isNaN(regression.getSumSquaredErrors()));
170         assertTrue("SSTO NaN", !Double.isNaN(regression.getTotalSumSquares()));
171         assertTrue("predict NaN", !Double.isNaN(regression.predict(0)));
172
173         regression.addData(1, 4);
174
175         // MSE, MSE, s(b0), s(b1) should all be OK now
176 assertTrue("MSE NaN", !Double.isNaN(regression.getMeanSquareError()));
177         assertTrue("slope std err NaN", !Double.isNaN(regression.getSlopeStdErr()));
178         assertTrue("intercept std err NaN", !Double.isNaN(regression.getInterceptStdErr()));
179     }
180
181     public void testClear() {
182         SimpleRegression regression = new SimpleRegression();
183         regression.addData(corrData);
184         assertEquals("number of observations", 17, regression.getN());
185         regression.clear();
186         assertEquals("number of observations", 0, regression.getN());
187         regression.addData(corrData);
188         assertEquals("r-square", .896123, regression.getRSquare(), 10E-6);
189         regression.addData(data);
190         assertEquals("number of observations", 53, regression.getN());
191     }
192
193     public void testInference() throws Exception JavaDoc {
194         //---------- verified against R, version 1.8.1 -----
195 // infData
196 SimpleRegression regression = new SimpleRegression();
197         regression.addData(infData);
198         assertEquals("slope std err", 0.011448491,
199                 regression.getSlopeStdErr(), 1E-10);
200         assertEquals("std err intercept", 0.286036932,
201                 regression.getInterceptStdErr(),1E-8);
202         assertEquals("significance", 4.596e-07,
203                 regression.getSignificance(),1E-8);
204         assertEquals("slope conf interval half-width", 0.0270713794287,
205                 regression.getSlopeConfidenceInterval(),1E-8);
206         // infData2
207 regression = new SimpleRegression();
208         regression.addData(infData2);
209         assertEquals("slope std err", 1.07260253,
210                 regression.getSlopeStdErr(), 1E-8);
211         assertEquals("std err intercept",4.17718672,
212                 regression.getInterceptStdErr(),1E-8);
213         assertEquals("significance", 0.261829133982,
214                 regression.getSignificance(),1E-11);
215         assertEquals("slope conf interval half-width", 2.97802204827,
216                 regression.getSlopeConfidenceInterval(),1E-8);
217         //------------- End R-verified tests -------------------------------
218
219         //FIXME: get a real example to test against with alpha = .01
220 assertTrue("tighter means wider",
221                 regression.getSlopeConfidenceInterval() < regression.getSlopeConfidenceInterval(0.01));
222      
223         try {
224             double x = regression.getSlopeConfidenceInterval(1);
225             fail("expecting IllegalArgumentException for alpha = 1");
226         } catch (IllegalArgumentException JavaDoc ex) {
227             ;
228         }
229
230     }
231
232     public void testPerfect() throws Exception JavaDoc {
233         SimpleRegression regression = new SimpleRegression();
234         int n = 100;
235         for (int i = 0; i < n; i++) {
236             regression.addData(((double) i) / (n - 1), i);
237         }
238         assertEquals(0.0, regression.getSignificance(), 1.0e-5);
239         assertTrue(regression.getSlope() > 0.0);
240     }
241
242     public void testPerfectNegative() throws Exception JavaDoc {
243         SimpleRegression regression = new SimpleRegression();
244         int n = 100;
245         for (int i = 0; i < n; i++) {
246             regression.addData(- ((double) i) / (n - 1), i);
247         }
248    
249         assertEquals(0.0, regression.getSignificance(), 1.0e-5);
250         assertTrue(regression.getSlope() < 0.0);
251     }
252
253     public void testRandom() throws Exception JavaDoc {
254         SimpleRegression regression = new SimpleRegression();
255         Random JavaDoc random = new Random JavaDoc(1);
256         int n = 100;
257         for (int i = 0; i < n; i++) {
258             regression.addData(((double) i) / (n - 1), random.nextDouble());
259         }
260
261         assertTrue( 0.0 < regression.getSignificance()
262                     && regression.getSignificance() < 1.0);
263     }
264 }
265
Popular Tags