@Test
public void test() {
final int n = 20;
final double[][] x = new double[n][5];
final double[] y1 = new double[n];
final double[] y2 = new double[n];
final double[] a1 = new double[] {3.4, 1.2, -0.62, -0.44, 0.65};
final double[] a2 = new double[] {0.98, 3.4, 1.2, -0.62, -0.44, 0.65};
for (int i = 0; i < n; i++) {
for (int j = 0; j < 5; j++) {
x[i][j] = RANDOM.nextDouble() + (RANDOM.nextDouble() - 0.5) / FACTOR;
}
y1[i] =
a1[0] * x[i][0]
+ a1[1] * x[i][1]
+ a1[2] * x[i][2]
+ a1[3] * x[i][3]
+ a1[4] * x[i][4]
+ RANDOM.nextDouble() / FACTOR;
y2[i] =
a2[0]
+ a2[1] * x[i][0]
+ a2[2] * x[i][1]
+ a2[3] * x[i][2]
+ a2[4] * x[i][3]
+ a2[5] * x[i][4]
+ RANDOM.nextDouble() / FACTOR;
}
final LeastSquaresRegressionResult result1 = REGRESSION.regress(x, null, y1, false);
final LeastSquaresRegressionResult result2 = REGRESSION.regress(x, null, y2, true);
assertRegression(result1, a1);
assertRegression(result2, a2);
final double[] residuals1 = result1.getResiduals();
for (int i = 0; i < n; i++) {
assertEquals(
y1[i],
a1[0] * x[i][0]
+ a1[1] * x[i][1]
+ a1[2] * x[i][2]
+ a1[3] * x[i][3]
+ a1[4] * x[i][4]
+ residuals1[i],
10 * EPS);
}
final double[] residuals2 = result2.getResiduals();
for (int i = 0; i < n; i++) {
assertEquals(
y2[i],
a2[0]
+ a2[1] * x[i][0]
+ a2[2] * x[i][1]
+ a2[3] * x[i][2]
+ a2[4] * x[i][3]
+ a2[5] * x[i][4]
+ residuals2[i],
10 * EPS);
}
}
@Test
public void test() {
final double[] y = new double[N];
final double[][] x = new double[N][3];
for (int i = 0; i < N; i++) {
y[i] = F2.evaluate(X[i]);
for (int j = 1; j < 3; j++) {
x[i][j] = X[i][j - 1];
}
x[i][0] = i % 2 == 0 ? -1. : 1.;
}
final LeastSquaresRegressionResult result = ADAPTIVE.regress(x, null, y, false);
final double[] betas = result.getBetas();
assertEquals(betas.length, 2);
assertEquals(betas[0], BETA_2, EPS);
assertEquals(betas[1], BETA_3, EPS);
}
