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17 package org.apache.commons.math.stat.regression;
18
19 import java.util.Random;
20
21 import junit.framework.Test;
22 import junit.framework.TestCase;
23 import junit.framework.TestSuite;
24
25
26
27
28
29
30 public final class SimpleRegressionTest extends TestCase {
31
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35
36
37 private double[][] data = { { 0.1, 0.2 }, {338.8, 337.4 }, {118.1, 118.2 },
38 {888.0, 884.6 }, {9.2, 10.1 }, {228.1, 226.5 }, {668.5, 666.3 }, {998.5, 996.3 },
39 {449.1, 448.6 }, {778.9, 777.0 }, {559.2, 558.2 }, {0.3, 0.4 }, {0.1, 0.6 }, {778.1, 775.5 },
40 {668.8, 666.9 }, {339.3, 338.0 }, {448.9, 447.5 }, {10.8, 11.6 }, {557.7, 556.0 },
41 {228.3, 228.1 }, {998.0, 995.8 }, {888.8, 887.6 }, {119.6, 120.2 }, {0.3, 0.3 },
42 {0.6, 0.3 }, {557.6, 556.8 }, {339.3, 339.1 }, {888.0, 887.2 }, {998.5, 999.0 },
43 {778.9, 779.0 }, {10.2, 11.1 }, {117.6, 118.3 }, {228.9, 229.2 }, {668.4, 669.1 },
44 {449.2, 448.9 }, {0.2, 0.5 }
45 };
46
47
48
49
50
51 private double[][] corrData = { { 101.0, 99.2 }, {100.1, 99.0 }, {100.0, 100.0 },
52 {90.6, 111.6 }, {86.5, 122.2 }, {89.7, 117.6 }, {90.6, 121.1 }, {82.8, 136.0 },
53 {70.1, 154.2 }, {65.4, 153.6 }, {61.3, 158.5 }, {62.5, 140.6 }, {63.6, 136.2 },
54 {52.6, 168.0 }, {59.7, 154.3 }, {59.5, 149.0 }, {61.3, 165.5 }
55 };
56
57
58
59
60
61 private double[][] infData = { { 15.6, 5.2 }, {26.8, 6.1 }, {37.8, 8.7 }, {36.4, 8.5 },
62 {35.5, 8.8 }, {18.6, 4.9 }, {15.3, 4.5 }, {7.9, 2.5 }, {0.0, 1.1 }
63 };
64
65
66
67
68 private double[][] infData2 = { { 1, 1 }, {2, 0 }, {3, 5 }, {4, 2 },
69 {5, -1 }, {6, 12 }
70 };
71
72 public SimpleRegressionTest(String name) {
73 super(name);
74 }
75
76 public void setUp() {
77 }
78
79 public static Test suite() {
80 TestSuite suite = new TestSuite(SimpleRegressionTest.class);
81 suite.setName("BivariateRegression Tests");
82 return suite;
83 }
84
85 public void testNorris() {
86 SimpleRegression regression = new SimpleRegression();
87 for (int i = 0; i < data.length; i++) {
88 regression.addData(data[i][1], data[i][0]);
89 }
90
91
92 assertEquals("slope", 1.00211681802045, regression.getSlope(), 10E-12);
93 assertEquals("slope std err", 0.429796848199937E-03,
94 regression.getSlopeStdErr(),10E-12);
95 assertEquals("number of observations", 36, regression.getN());
96 assertEquals( "intercept", -0.262323073774029,
97 regression.getIntercept(),10E-12);
98 assertEquals("std err intercept", 0.232818234301152,
99 regression.getInterceptStdErr(),10E-12);
100 assertEquals("r-square", 0.999993745883712,
101 regression.getRSquare(), 10E-12);
102 assertEquals("SSR", 4255954.13232369,
103 regression.getRegressionSumSquares(), 10E-9);
104 assertEquals("MSE", 0.782864662630069,
105 regression.getMeanSquareError(), 10E-10);
106 assertEquals("SSE", 26.6173985294224,
107 regression.getSumSquaredErrors(),10E-9);
108
109
110 assertEquals( "predict(0)", -0.262323073774029,
111 regression.predict(0), 10E-12);
112 assertEquals("predict(1)", 1.00211681802045 - 0.262323073774029,
113 regression.predict(1), 10E-12);
114 }
115
116 public void testCorr() {
117 SimpleRegression regression = new SimpleRegression();
118 regression.addData(corrData);
119 assertEquals("number of observations", 17, regression.getN());
120 assertEquals("r-square", .896123, regression.getRSquare(), 10E-6);
121 assertEquals("r", -0.94663767742, regression.getR(), 1E-10);
122 }
123
124 public void testNaNs() {
125 SimpleRegression regression = new SimpleRegression();
126 assertTrue("intercept not NaN", Double.isNaN(regression.getIntercept()));
127 assertTrue("slope not NaN", Double.isNaN(regression.getSlope()));
128 assertTrue("slope std err not NaN", Double.isNaN(regression.getSlopeStdErr()));
129 assertTrue("intercept std err not NaN", Double.isNaN(regression.getInterceptStdErr()));
130 assertTrue("MSE not NaN", Double.isNaN(regression.getMeanSquareError()));
131 assertTrue("e not NaN", Double.isNaN(regression.getR()));
132 assertTrue("r-square not NaN", Double.isNaN(regression.getRSquare()));
133 assertTrue( "RSS not NaN", Double.isNaN(regression.getRegressionSumSquares()));
134 assertTrue("SSE not NaN",Double.isNaN(regression.getSumSquaredErrors()));
135 assertTrue("SSTO not NaN", Double.isNaN(regression.getTotalSumSquares()));
136 assertTrue("predict not NaN", Double.isNaN(regression.predict(0)));
137
138 regression.addData(1, 2);
139 regression.addData(1, 3);
140
141
142 assertTrue("intercept not NaN", Double.isNaN(regression.getIntercept()));
143 assertTrue("slope not NaN", Double.isNaN(regression.getSlope()));
144 assertTrue("slope std err not NaN", Double.isNaN(regression.getSlopeStdErr()));
145 assertTrue("intercept std err not NaN", Double.isNaN(regression.getInterceptStdErr()));
146 assertTrue("MSE not NaN", Double.isNaN(regression.getMeanSquareError()));
147 assertTrue("e not NaN", Double.isNaN(regression.getR()));
148 assertTrue("r-square not NaN", Double.isNaN(regression.getRSquare()));
149 assertTrue("RSS not NaN", Double.isNaN(regression.getRegressionSumSquares()));
150 assertTrue("SSE not NaN", Double.isNaN(regression.getSumSquaredErrors()));
151 assertTrue("predict not NaN", Double.isNaN(regression.predict(0)));
152
153
154 assertTrue("SSTO NaN", !Double.isNaN(regression.getTotalSumSquares()));
155
156 regression = new SimpleRegression();
157
158 regression.addData(1, 2);
159 regression.addData(3, 3);
160
161
162 assertTrue("interceptNaN", !Double.isNaN(regression.getIntercept()));
163 assertTrue("slope NaN", !Double.isNaN(regression.getSlope()));
164 assertTrue ("slope std err not NaN", Double.isNaN(regression.getSlopeStdErr()));
165 assertTrue("intercept std err not NaN", Double.isNaN(regression.getInterceptStdErr()));
166 assertTrue("MSE not NaN", Double.isNaN(regression.getMeanSquareError()));
167 assertTrue("r NaN", !Double.isNaN(regression.getR()));
168 assertTrue("r-square NaN", !Double.isNaN(regression.getRSquare()));
169 assertTrue("RSS NaN", !Double.isNaN(regression.getRegressionSumSquares()));
170 assertTrue("SSE NaN", !Double.isNaN(regression.getSumSquaredErrors()));
171 assertTrue("SSTO NaN", !Double.isNaN(regression.getTotalSumSquares()));
172 assertTrue("predict NaN", !Double.isNaN(regression.predict(0)));
173
174 regression.addData(1, 4);
175
176
177 assertTrue("MSE NaN", !Double.isNaN(regression.getMeanSquareError()));
178 assertTrue("slope std err NaN", !Double.isNaN(regression.getSlopeStdErr()));
179 assertTrue("intercept std err NaN", !Double.isNaN(regression.getInterceptStdErr()));
180 }
181
182 public void testClear() {
183 SimpleRegression regression = new SimpleRegression();
184 regression.addData(corrData);
185 assertEquals("number of observations", 17, regression.getN());
186 regression.clear();
187 assertEquals("number of observations", 0, regression.getN());
188 regression.addData(corrData);
189 assertEquals("r-square", .896123, regression.getRSquare(), 10E-6);
190 regression.addData(data);
191 assertEquals("number of observations", 53, regression.getN());
192 }
193
194 public void testInference() throws Exception {
195
196
197 SimpleRegression regression = new SimpleRegression();
198 regression.addData(infData);
199 assertEquals("slope std err", 0.011448491,
200 regression.getSlopeStdErr(), 1E-10);
201 assertEquals("std err intercept", 0.286036932,
202 regression.getInterceptStdErr(),1E-8);
203 assertEquals("significance", 4.596e-07,
204 regression.getSignificance(),1E-8);
205 assertEquals("slope conf interval half-width", 0.0270713794287,
206 regression.getSlopeConfidenceInterval(),1E-8);
207
208 regression = new SimpleRegression();
209 regression.addData(infData2);
210 assertEquals("slope std err", 1.07260253,
211 regression.getSlopeStdErr(), 1E-8);
212 assertEquals("std err intercept",4.17718672,
213 regression.getInterceptStdErr(),1E-8);
214 assertEquals("significance", 0.261829133982,
215 regression.getSignificance(),1E-11);
216 assertEquals("slope conf interval half-width", 2.97802204827,
217 regression.getSlopeConfidenceInterval(),1E-8);
218
219
220
221 assertTrue("tighter means wider",
222 regression.getSlopeConfidenceInterval() < regression.getSlopeConfidenceInterval(0.01));
223
224 try {
225 regression.getSlopeConfidenceInterval(1);
226 fail("expecting IllegalArgumentException for alpha = 1");
227 } catch (IllegalArgumentException ex) {
228 ;
229 }
230
231 }
232
233 public void testPerfect() throws Exception {
234 SimpleRegression regression = new SimpleRegression();
235 int n = 100;
236 for (int i = 0; i < n; i++) {
237 regression.addData(((double) i) / (n - 1), i);
238 }
239 assertEquals(0.0, regression.getSignificance(), 1.0e-5);
240 assertTrue(regression.getSlope() > 0.0);
241 assertTrue(regression.getSumSquaredErrors() >= 0.0);
242 }
243
244 public void testPerfectNegative() throws Exception {
245 SimpleRegression regression = new SimpleRegression();
246 int n = 100;
247 for (int i = 0; i < n; i++) {
248 regression.addData(- ((double) i) / (n - 1), i);
249 }
250
251 assertEquals(0.0, regression.getSignificance(), 1.0e-5);
252 assertTrue(regression.getSlope() < 0.0);
253 }
254
255 public void testRandom() throws Exception {
256 SimpleRegression regression = new SimpleRegression();
257 Random random = new Random(1);
258 int n = 100;
259 for (int i = 0; i < n; i++) {
260 regression.addData(((double) i) / (n - 1), random.nextDouble());
261 }
262
263 assertTrue( 0.0 < regression.getSignificance()
264 && regression.getSignificance() < 1.0);
265 }
266
267
268
269 public void testSSENonNegative() {
270 double[] y = { 8915.102, 8919.302, 8923.502 };
271 double[] x = { 1.107178495E2, 1.107264895E2, 1.107351295E2 };
272 SimpleRegression reg = new SimpleRegression();
273 for (int i = 0; i < x.length; i++) {
274 reg.addData(x[i], y[i]);
275 }
276 assertTrue(reg.getSumSquaredErrors() >= 0.0);
277 }
278 }