Package com.opengamma.analytics.math.statistics.leastsquare

Examples of com.opengamma.analytics.math.statistics.leastsquare.LeastSquareResults

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      getCalibrationObjective().setPrice(prices);
      objective.setStartIndex(_instrumentIndex.get(loopblock * _nbInstrumentsBlock));
      objective.setEndIndex(_instrumentIndex.get((loopblock + 1) * _nbInstrumentsBlock) - 1);
      // Implementation note: the index start is from the first instrument of the block and the index end is from the last instrument of the block.
      final DoubleMatrix1D observedValues = new DoubleMatrix1D(_nbInstrumentsBlock, 0.0);
      @SuppressWarnings("unused")
      final
      LeastSquareResults result = ls.solve(observedValues, getCalibrationObjective(), new DoubleMatrix1D(1.0, 0.0));
      // Implementation note: the start value is a multiplicative factor of one and an additive term of 0 (parameters unchanged).
      //   The observed values are 0 as the function returns the difference between the calculated prices and the targets.
    }
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    _nKnotPoints = sum;

  }

  public LeastSquareResultsWithTransform solve(final DoubleMatrix1D start) {
    final LeastSquareResults lsRes = SOLVER.solve(_vols, _errors, getModelValueFunction(), getModelJacobianFunction(), start);
    return new LeastSquareResultsWithTransform(lsRes, new UncoupledParameterTransforms(start, getTransforms(), new BitSet(start.getNumberOfElements())));
  }
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      _calibrationObjective.setPrice(prices);
      objective.setStartIndex(_instrumentIndex.get(loopblock * _nbInstrumentsBlock));
      objective.setEndIndex(_instrumentIndex.get((loopblock + 1) * _nbInstrumentsBlock) - 1);
      // Implementation note: the index start is from the first instrument of the block and the index end is from the last instrument of the block.
      final DoubleMatrix1D observedValues = new DoubleMatrix1D(_nbInstrumentsBlock, 0.0);
      @SuppressWarnings("unused")
      final
      LeastSquareResults result = ls.solve(observedValues, _calibrationObjective, new DoubleMatrix1D(1.0, 0.0));
      // Implementation note: the start value is a multiplicative factor of one and an additive term of 0 (parameters unchanged).
      //   The observed values are 0 as the function returns the difference between the calculated prices and the targets.
    }
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      }
    };

    //TODO replace this with an explicit polynomial fitter
    final NonLinearLeastSquare ls = new NonLinearLeastSquare();
    final LeastSquareResults lsRes = ls.solve(new DoubleMatrix1D(x), new DoubleMatrix1D(impliedVols), func, new DoubleMatrix1D(0.1, 0.0, 0.0));
    final DoubleMatrix1D fitP = lsRes.getFitParameters();
    return fitP;
  }
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    final ConjugateDirectionVectorMinimizer minimzer = new ConjugateDirectionVectorMinimizer(lineMinimizer, 1e-6, 10000);
    final DoubleMatrix1D fp = transforms.transform(new DoubleMatrix1D(initialFitParameters));
    final DoubleMatrix1D minPos = minimzer.minimize(function, fp);
    final double chiSquare = function.evaluate(minPos);
    final DoubleMatrix1D res = transforms.inverseTransform(minPos);
    return new LeastSquareResultsWithTransform(new LeastSquareResults(chiSquare, res, new DoubleMatrix2D(new double[N_PARAMETERS][N_PARAMETERS])), transforms);
    // return new LeastSquareResults(chiSquare, res, new DoubleMatrix2D(new double[N_PARAMETERS][N_PARAMETERS]));
  }
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      sigma[i] = 0.01; //1% error
    }

    final NonLinearLeastSquare ls = new NonLinearLeastSquare();
    //solve approx first
    LeastSquareResults solverRes = ls.solve(new DoubleMatrix1D(mrkVols), new DoubleMatrix1D(sigma), funcAppox, TRANSFORMS.transform(initialGuess));
    // now solve pde model
    solverRes = ls.solve(new DoubleMatrix1D(mrkVols), new DoubleMatrix1D(sigma), func, solverRes.getFitParameters());
    return new LeastSquareResultsWithTransform(solverRes, TRANSFORMS);
  }
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        return FORMULA.getVolatilityFunction(new EuropeanVanillaOption(strike, maturity, true), forward).evaluate(newData);
      }
    };

    final DoubleMatrix1D fp = transforms.transform(new DoubleMatrix1D(initialFitParameters));
    final LeastSquareResults lsRes = errors == null ? _solver.solve(new DoubleMatrix1D(strikes), new DoubleMatrix1D(blackVols), function, fp) : _solver.solve(new DoubleMatrix1D(strikes),
        new DoubleMatrix1D(blackVols), new DoubleMatrix1D(errors), function, fp);
    // final DoubleMatrix1D mp = transforms.inverseTransform(lsRes.getFitParameters());
    return new LeastSquareResultsWithTransform(lsRes, transforms);
    // return new LeastSquareResults(lsRes.getChiSq(), mp, new DoubleMatrix2D(new double[N_PARAMETERS][N_PARAMETERS]));
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   * @return The LeastSquareResults
   */
  public LeastSquareResultsWithTransform solve(final DoubleMatrix1D start, final NonLinearParameterTransforms transform) {
    final NonLinearTransformFunction transFunc = new NonLinearTransformFunction(getModelValueFunction(), getModelJacobianFunction(), transform);

    final LeastSquareResults solRes = SOLVER.solve(_marketValues, _errors, transFunc.getFittingFunction(), transFunc.getFittingJacobian(),
        transform.transform(start), getConstraintFunction(transform), getMaximumStep());
    return new LeastSquareResultsWithTransform(solRes, transform);
  }
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        return _formula.getVolatilityFunction(option, forward).evaluate(sabrFormulaData);
      }
    };

    final DoubleMatrix1D fp = transforms.transform(new DoubleMatrix1D(initialFitParameters));
    LeastSquareResults lsRes = errors == null ? SOLVER.solve(new DoubleMatrix1D(strikes), new DoubleMatrix1D(blackVols), function, fp)
        : SOLVER.solve(new DoubleMatrix1D(strikes), new DoubleMatrix1D(blackVols), new DoubleMatrix1D(errors), function, fp);
    final double[] mp = transforms.inverseTransform(lsRes.getFitParameters()).toArray();
    if (recoverATMVol) {
      final double beta = mp[1];
      final double nu = mp[2];
      final double rho = mp[3];
      final EuropeanVanillaOption option = new EuropeanVanillaOption(forward, maturity, true);
      final SABRFormulaData sabrFormulaData = new SABRFormulaData(mp[0], beta, rho, nu);
      final double value = _atmCalculator.calculate(sabrFormulaData, option, forward, atmVol);
      mp[0] = value;
      lsRes = new LeastSquareResults(lsRes.getChiSq(), new DoubleMatrix1D(mp), lsRes.getCovariance());
    }
    return new LeastSquareResultsWithTransform(lsRes, transforms);
    //return new LeastSquareResults(lsRes.getChiSq(), new DoubleMatrix1D(mp), new DoubleMatrix2D(new double[N_PARAMETERS][N_PARAMETERS]), lsRes.getFittingParameterSensitivityToData());
  }
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        1.9259326343836376, 1.9868728791190922, 2.0441767092857317, 2.0982583238541026, 2.1494622372820675, 2.198020785622251, 2.244237863291375 };
    final int n = strikes.length;
    final double[] errors = new double[n];
    Arrays.fill(errors, 0.01); //1% error
    final SmileModelFitter<T> fitter = getFitter(forward, strikes, expiry, vols, errors, getModel());
    LeastSquareResults best = null;
    final BitSet fixed = new BitSet();
    for (int i = 0; i < 5; i++) {
      final double[] start = getRandomStartValues();

      //   int nStartPoints = start.length;
      final LeastSquareResults lsRes = fitter.solve(new DoubleMatrix1D(start), fixed);
      //     System.out.println(this.toString() + lsRes.toString());
      if (best == null) {
        best = lsRes;
      } else {
        if (lsRes.getChiSq() < best.getChiSq()) {
          best = lsRes;
        }
      }
    }
    //
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Related Classes of com.opengamma.analytics.math.statistics.leastsquare.LeastSquareResults

  • com.opengamma.analytics.financial.interestrate.capletstripping.CapletStrippingAbsoluteStrikePSpline
  • com.opengamma.analytics.financial.interestrate.capletstripping.CapletStrippingMarketDataTest
  • com.opengamma.analytics.financial.interestrate.capletstripping.CapletStrippingSingleStrikeDirect
  • com.opengamma.analytics.financial.interestrate.capletstripping.CapletStrippingTest
  • com.opengamma.analytics.financial.interestrate.NelsonSiegelBondCurveModelTest
  • com.opengamma.analytics.financial.interestrate.NelsonSiegelSvenssonBondCurveModelTest
  • com.opengamma.analytics.financial.interestrate.swaption.method.SwaptionPhysicalLMMDDSuccessiveLeastSquareCalibrationEngine
  • com.opengamma.analytics.financial.model.finitedifference.applications.TwoStateMarkovChainFitter
  • com.opengamma.analytics.financial.model.volatility.local.LocalVolFittingTest
  • com.opengamma.analytics.financial.model.volatility.smile.fitting.interpolation.SmileInterpolator
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