Examples of GaussNewtonEstimator

org.apache.commons.math.estimation.GaussNewtonEstimator
This class implements a solver for estimation problems.
This class solves estimation problems using a weighted least squares criterion on the measurement residuals. It uses a Gauss-Newton algorithm.
@version $Revision: 990655 $ $Date: 2010-08-29 23:49:40 +0200 (dim. 29 août 2010) $ @since 1.2 @deprecated as of 2.0, everything in package org.apache.commons.math.estimation hasbeen deprecated and replaced by package org.apache.commons.math.optimization.general

Examples of org.apache.commons.math.estimation.GaussNewtonEstimator

        new LinearMeasurement(new double[] {2},
                              new EstimatedParameter[] {
                                 new EstimatedParameter("p0", 0)
                              }, 3.0)
      });
    GaussNewtonEstimator estimator = new GaussNewtonEstimator(100, 1.0e-6, 1.0e-6);
    estimator.estimate(problem);
    assertEquals(0, estimator.getRMS(problem), 1.0e-10);
    assertEquals(1.5,
                 problem.getUnboundParameters()[0].getEstimate(),
                 1.0e-10);
   }

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Examples of org.apache.commons.math.estimation.GaussNewtonEstimator

      new LinearMeasurement(new double[] { 1.0, -2.0 },
                            new EstimatedParameter[] { x[0], x[1] },
                            1.0)
    });


    GaussNewtonEstimator estimator = new GaussNewtonEstimator(100, 1.0e-6, 1.0e-6);
    estimator.estimate(problem);
    assertEquals(0, estimator.getRMS(problem), 1.0e-10);
    assertEquals(7.0, x[0].getEstimate(), 1.0e-10);
    assertEquals(3.0, x[1].getEstimate(), 1.0e-10);


  }

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Examples of org.apache.commons.math.estimation.GaussNewtonEstimator

      new LinearMeasurement(new double[] {2}, new EstimatedParameter[] { p[2] }, 2.2),
      new LinearMeasurement(new double[] {2}, new EstimatedParameter[] { p[3] }, 3.3),
      new LinearMeasurement(new double[] {2}, new EstimatedParameter[] { p[4] }, 4.4),
      new LinearMeasurement(new double[] {2}, new EstimatedParameter[] { p[5] }, 5.5)
    });
  GaussNewtonEstimator estimator = new GaussNewtonEstimator(100, 1.0e-6, 1.0e-6);
  estimator.estimate(problem);
  assertEquals(0, estimator.getRMS(problem), 1.0e-10);
  for (int i = 0; i < p.length; ++i) {
    assertEquals(0.55 * i, p[i].getEstimate(), 1.0e-10);
  }
}

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Examples of org.apache.commons.math.estimation.GaussNewtonEstimator

      new LinearMeasurement(new double[] { -1.0, 1.0 },
                            new EstimatedParameter[] { p[1], p[2] },
                            1.0)
    });


    GaussNewtonEstimator estimator = new GaussNewtonEstimator(100, 1.0e-6, 1.0e-6);
    estimator.estimate(problem);
    assertEquals(0, estimator.getRMS(problem), 1.0e-10);
    assertEquals(1.0, p[0].getEstimate(), 1.0e-10);
    assertEquals(2.0, p[1].getEstimate(), 1.0e-10);
    assertEquals(3.0, p[2].getEstimate(), 1.0e-10);


  }

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Examples of org.apache.commons.math.estimation.GaussNewtonEstimator

                            new EstimatedParameter[] { p[4], p[5] },
                            2.0)


    });


    GaussNewtonEstimator estimator = new GaussNewtonEstimator(100, 1.0e-6, 1.0e-6);
    estimator.estimate(problem);
    assertEquals(0, estimator.getRMS(problem), 1.0e-10);
    assertEquals( 3.0, p[0].getEstimate(), 1.0e-10);
    assertEquals( 4.0, p[1].getEstimate(), 1.0e-10);
    assertEquals(-1.0, p[2].getEstimate(), 1.0e-10);
    assertEquals(-2.0, p[3].getEstimate(), 1.0e-10);
    assertEquals( 1.0 + epsilon, p[4].getEstimate(), 1.0e-10);

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Examples of org.apache.commons.math.estimation.GaussNewtonEstimator

                            new EstimatedParameter[] { p[0], p[2] },
                            1.0)
    };
    LinearProblem problem = new LinearProblem(m);


    GaussNewtonEstimator estimator = new GaussNewtonEstimator(100, 1.0e-6, 1.0e-6);
    try {
      estimator.estimate(problem);
      fail("an exception should have been caught");
    } catch (EstimationException ee) {
      // expected behavior
    } catch (Exception e) {
      fail("wrong exception type caught");

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Examples of org.apache.commons.math.estimation.GaussNewtonEstimator

                            33.0),
      new LinearMeasurement(new double[] {  7.0, 5.0,  9.0, 10.0 },
                            new EstimatedParameter[] { p[0], p[1], p[2], p[3] },
                            31.0)
    });
    GaussNewtonEstimator estimator1 = new GaussNewtonEstimator(100, 1.0e-6, 1.0e-6);
    estimator1.estimate(problem1);
    assertEquals(0, estimator1.getRMS(problem1), 1.0e-10);
    assertEquals(1.0, p[0].getEstimate(), 1.0e-10);
    assertEquals(1.0, p[1].getEstimate(), 1.0e-10);
    assertEquals(1.0, p[2].getEstimate(), 1.0e-10);
    assertEquals(1.0, p[3].getEstimate(), 1.0e-10);


    LinearProblem problem2 = new LinearProblem(new LinearMeasurement[] {
      new LinearMeasurement(new double[] { 10.0, 7.0,  8.1,  7.2 },
                            new EstimatedParameter[] { p[0], p[1], p[2], p[3] },
                            32.0),
      new LinearMeasurement(new double[] {  7.08, 5.04,  6.0,  5.0 },
                            new EstimatedParameter[] { p[0], p[1], p[2], p[3] },
                            23.0),
      new LinearMeasurement(new double[] {  8.0, 5.98, 9.89,  9.0 },
                             new EstimatedParameter[] { p[0], p[1], p[2], p[3] },
                            33.0),
      new LinearMeasurement(new double[] {  6.99, 4.99,  9.0, 9.98 },
                             new EstimatedParameter[] { p[0], p[1], p[2], p[3] },
                            31.0)
    });
    GaussNewtonEstimator estimator2 = new GaussNewtonEstimator(100, 1.0e-6, 1.0e-6);
    estimator2.estimate(problem2);
    assertEquals(0, estimator2.getRMS(problem2), 1.0e-10);
    assertEquals(-81.0, p[0].getEstimate(), 1.0e-8);
    assertEquals(137.0, p[1].getEstimate(), 1.0e-8);
    assertEquals(-34.0, p[2].getEstimate(), 1.0e-8);
    assertEquals( 22.0, p[3].getEstimate(), 1.0e-8);

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Examples of org.apache.commons.math.estimation.GaussNewtonEstimator

      new LinearMeasurement(new double[] { 2.0, 1.0 },
                             new EstimatedParameter[] { p[0], p[2] },
                             5.0)
    });


    GaussNewtonEstimator estimator = new GaussNewtonEstimator(100, 1.0e-6, 1.0e-6);
    try {
        estimator.estimate(problem);
        fail("an exception should have been caught");
    } catch (EstimationException ee) {
        // expected behavior
    } catch (Exception e) {
        fail("wrong exception type caught");

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Examples of org.apache.commons.math.estimation.GaussNewtonEstimator

      new LinearMeasurement(new double[] { 1.0, -1.0 },
                           new EstimatedParameter[] { p[4], p[3] },
                           1.0)
    });


    GaussNewtonEstimator estimator = new GaussNewtonEstimator(100, 1.0e-6, 1.0e-6);
    try {
        estimator.estimate(problem);
        fail("an exception should have been caught");
    } catch (EstimationException ee) {
        // expected behavior
    } catch (Exception e) {
        fail("wrong exception type caught");

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Examples of org.apache.commons.math.estimation.GaussNewtonEstimator

      new LinearMeasurement(new double[] { 1.0, 3.0 },
                             new EstimatedParameter[] { p[0], p[1] },
                             5.0)
    });


    GaussNewtonEstimator estimator = new GaussNewtonEstimator(100, 1.0e-6, 1.0e-6);
    estimator.estimate(problem);
    assertEquals(0, estimator.getRMS(problem), 1.0e-10);
    EstimatedParameter[] all = problem.getAllParameters();
    for (int i = 0; i < all.length; ++i) {
        assertEquals(all[i].getName().equals("p0") ? 2.0 : 1.0,
                     all[i].getEstimate(), 1.0e-10);
    }

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