public void testNaNs() {
SimpleRegression regression = new SimpleRegression();
assertTrue("intercept not NaN", Double.isNaN(regression.getIntercept()));
assertTrue("slope not NaN", Double.isNaN(regression.getSlope()));
assertTrue("slope std err not NaN", Double.isNaN(regression.getSlopeStdErr()));
assertTrue("intercept std err not NaN", Double.isNaN(regression.getInterceptStdErr()));
assertTrue("MSE not NaN", Double.isNaN(regression.getMeanSquareError()));
assertTrue("e not NaN", Double.isNaN(regression.getR()));
assertTrue("r-square not NaN", Double.isNaN(regression.getRSquare()));
assertTrue("RSS not NaN", Double.isNaN(regression.getRegressionSumSquares()));
assertTrue("SSE not NaN", Double.isNaN(regression.getSumSquaredErrors()));
assertTrue("SSTO not NaN", Double.isNaN(regression.getTotalSumSquares()));
assertTrue("predict not NaN", Double.isNaN(regression.predict(0)));
regression.addData(1, 2);
regression.addData(1, 3);
// No x variation, so these should still blow...
assertTrue("intercept not NaN", Double.isNaN(regression.getIntercept()));
assertTrue("slope not NaN", Double.isNaN(regression.getSlope()));
assertTrue("slope std err not NaN", Double.isNaN(regression.getSlopeStdErr()));
assertTrue("intercept std err not NaN", Double.isNaN(regression.getInterceptStdErr()));
assertTrue("MSE not NaN", Double.isNaN(regression.getMeanSquareError()));
assertTrue("e not NaN", Double.isNaN(regression.getR()));
assertTrue("r-square not NaN", Double.isNaN(regression.getRSquare()));
assertTrue("RSS not NaN", Double.isNaN(regression.getRegressionSumSquares()));
assertTrue("SSE not NaN", Double.isNaN(regression.getSumSquaredErrors()));
assertTrue("predict not NaN", Double.isNaN(regression.predict(0)));
// but SSTO should be OK
assertTrue("SSTO NaN", !Double.isNaN(regression.getTotalSumSquares()));
regression = new SimpleRegression();
regression.addData(1, 2);
regression.addData(3, 3);
// All should be OK except MSE, s(b0), s(b1) which need one more df
assertTrue("interceptNaN", !Double.isNaN(regression.getIntercept()));
assertTrue("slope NaN", !Double.isNaN(regression.getSlope()));
assertTrue("slope std err not NaN", Double.isNaN(regression.getSlopeStdErr()));
assertTrue("intercept std err not NaN", Double.isNaN(regression.getInterceptStdErr()));
assertTrue("MSE not NaN", Double.isNaN(regression.getMeanSquareError()));
assertTrue("r NaN", !Double.isNaN(regression.getR()));
assertTrue("r-square NaN", !Double.isNaN(regression.getRSquare()));
assertTrue("RSS NaN", !Double.isNaN(regression.getRegressionSumSquares()));
assertTrue("SSE NaN", !Double.isNaN(regression.getSumSquaredErrors()));
assertTrue("SSTO NaN", !Double.isNaN(regression.getTotalSumSquares()));
assertTrue("predict NaN", !Double.isNaN(regression.predict(0)));
regression.addData(1, 4);
// MSE, MSE, s(b0), s(b1) should all be OK now
assertTrue("MSE NaN", !Double.isNaN(regression.getMeanSquareError()));
assertTrue("slope std err NaN", !Double.isNaN(regression.getSlopeStdErr()));
assertTrue("intercept std err NaN", !Double.isNaN(regression.getInterceptStdErr()));
}
public void testInference() throws Exception {
// ---------- verified against R, version 1.8.1 -----
// infData
SimpleRegression regression = new SimpleRegression();
regression.addData(infData);
assertEquals("slope std err", 0.011448491, regression.getSlopeStdErr(), 1E-10);
assertEquals("std err intercept", 0.286036932, regression.getInterceptStdErr(), 1E-8);
assertEquals("significance", 4.596e-07, regression.getSignificance(), 1E-8);
assertEquals(
"slope conf interval half-width",
0.0270713794287,
regression.getSlopeConfidenceInterval(),
1E-8);
// infData2
regression = new SimpleRegression();
regression.addData(infData2);
assertEquals("slope std err", 1.07260253, regression.getSlopeStdErr(), 1E-8);
assertEquals("std err intercept", 4.17718672, regression.getInterceptStdErr(), 1E-8);
assertEquals("significance", 0.261829133982, regression.getSignificance(), 1E-11);
assertEquals(
"slope conf interval half-width",
2.97802204827,
regression.getSlopeConfidenceInterval(),
1E-8);
// ------------- End R-verified tests -------------------------------
// FIXME: get a real example to test against with alpha = .01
assertTrue(
"tighter means wider",
regression.getSlopeConfidenceInterval() < regression.getSlopeConfidenceInterval(0.01));
try {
regression.getSlopeConfidenceInterval(1);
fail("expecting IllegalArgumentException for alpha = 1");
} catch (IllegalArgumentException ex) {
// ignored
}
}
// Test remove multiple observations
public void testRemoveMultiple() throws Exception {
// Create regression with inference data then remove to test
SimpleRegression regression = new SimpleRegression();
regression.addData(infData);
regression.removeData(removeMultiple);
regression.addData(removeMultiple);
// Use the inference assertions to make sure that everything worked
assertEquals("slope std err", 0.011448491, regression.getSlopeStdErr(), 1E-10);
assertEquals("std err intercept", 0.286036932, regression.getInterceptStdErr(), 1E-8);
assertEquals("significance", 4.596e-07, regression.getSignificance(), 1E-8);
assertEquals(
"slope conf interval half-width",
0.0270713794287,
regression.getSlopeConfidenceInterval(),
1E-8);
}
public void testNorris() {
SimpleRegression regression = new SimpleRegression();
for (int i = 0; i < data.length; i++) {
regression.addData(data[i][1], data[i][0]);
}
// Tests against certified values from
// http://www.itl.nist.gov/div898/strd/lls/data/LINKS/DATA/Norris.dat
assertEquals("slope", 1.00211681802045, regression.getSlope(), 10E-12);
assertEquals("slope std err", 0.429796848199937E-03, regression.getSlopeStdErr(), 10E-12);
assertEquals("number of observations", 36, regression.getN());
assertEquals("intercept", -0.262323073774029, regression.getIntercept(), 10E-12);
assertEquals("std err intercept", 0.232818234301152, regression.getInterceptStdErr(), 10E-12);
assertEquals("r-square", 0.999993745883712, regression.getRSquare(), 10E-12);
assertEquals("SSR", 4255954.13232369, regression.getRegressionSumSquares(), 10E-9);
assertEquals("MSE", 0.782864662630069, regression.getMeanSquareError(), 10E-10);
assertEquals("SSE", 26.6173985294224, regression.getSumSquaredErrors(), 10E-9);
// ------------ End certified data tests
assertEquals("predict(0)", -0.262323073774029, regression.predict(0), 10E-12);
assertEquals("predict(1)", 1.00211681802045 - 0.262323073774029, regression.predict(1), 10E-12);
}