Example usage for org.apache.commons.math3.optim.univariate MultiStartUnivariateOptimizer MultiStartUnivariateOptimizer

Introduction

In this page you can find the example usage for org.apache.commons.math3.optim.univariate MultiStartUnivariateOptimizer MultiStartUnivariateOptimizer.

Prototype

public MultiStartUnivariateOptimizer(final UnivariateOptimizer optimizer, final int starts,
        final RandomGenerator generator) 

Source Link

Document

Create a multi-start optimizer from a single-start optimizer.

Usage

From source file:com.itemanalysis.psychometrics.irt.equating.IrtScaleLinking.java

public void computeCoefficients() {
    raschFamily = checkRaschModel();//w w  w  . ja v a 2  s.com

    ms.setPrecision(precision);
    mm.setPrecision(precision);
    hb.setPrecision(precision);
    sl.setPrecision(precision);

    if (raschFamily) {

        double[] sv = { mm.getIntercept() };

        UnivariateOptimizer underlying = new BrentOptimizer(1e-10, 1e-14);
        JDKRandomGenerator g = new JDKRandomGenerator();

        //Haebara method
        MultiStartUnivariateOptimizer optimizer = new MultiStartUnivariateOptimizer(underlying, 5, g);//Five random starts to Brent optimizer.
        UnivariatePointValuePair hbPair = optimizer.optimize(new MaxEval(500),
                new UnivariateObjectiveFunction(hb), GoalType.MINIMIZE, new SearchInterval(-4, 4),
                new InitialGuess(sv));
        hb.setIntercept(hbPair.getPoint());
        hb.setScale(1.0);
        fHB = hbPair.getValue();

        //Stocking-Lord method
        UnivariatePointValuePair slPair = optimizer.optimize(new MaxEval(500),
                new UnivariateObjectiveFunction(sl), GoalType.MINIMIZE, new SearchInterval(-4, 4),
                new InitialGuess(sv));
        sl.setIntercept(slPair.getPoint());
        sl.setScale(1.0);
        fSL = slPair.getValue();

    } else {

        double[] hbStartValues = { mm.getIntercept(), mm.getScale() };
        double[] slStartValues = { mm.getIntercept(), mm.getScale() };

        if (useUncmin) {
            DefaultUncminOptimizer optimizer = new DefaultUncminOptimizer();

            try {

                optimizer.minimize(hb, hbStartValues);
                double[] param = optimizer.getParameters();
                fHB = optimizer.getFunctionValue();
                hb.setIntercept(param[0]);

                if (param.length > 1) {
                    hb.setScale(param[1]);
                } else {
                    hb.setScale(1.0);//Rasch family of models
                }

                optimizer.minimize(sl, slStartValues);
                param = optimizer.getParameters();
                fSL = optimizer.getFunctionValue();
                sl.setIntercept(param[0]);

                if (param.length > 1) {
                    sl.setScale(param[1]);
                } else {
                    sl.setScale(1.0);//Rasch family of models
                }

            } catch (UncminException ex) {
                ex.printStackTrace();
            }
        } else {

            int numIterpolationPoints = 2 * 2;//two dimensions A and B
            BOBYQAOptimizer underlying = new BOBYQAOptimizer(numIterpolationPoints);
            RandomGenerator g = new JDKRandomGenerator();
            RandomVectorGenerator generator = new UncorrelatedRandomVectorGenerator(2,
                    new GaussianRandomGenerator(g));
            MultiStartMultivariateOptimizer optimizer = new MultiStartMultivariateOptimizer(underlying, 10,
                    generator);
            PointValuePair hbOptimum = optimizer.optimize(new MaxEval(1000), new ObjectiveFunction(hb),
                    GoalType.MINIMIZE, SimpleBounds.unbounded(2), new InitialGuess(hbStartValues));

            double[] hbCoefficients = hbOptimum.getPoint();
            hb.setIntercept(hbCoefficients[0]);
            hb.setScale(hbCoefficients[1]);
            fHB = hbOptimum.getValue();

            PointValuePair slOptimum = optimizer.optimize(new MaxEval(1000), new ObjectiveFunction(sl),
                    GoalType.MINIMIZE, SimpleBounds.unbounded(2), new InitialGuess(slStartValues));

            double[] slCoefficients = slOptimum.getPoint();
            sl.setIntercept(slCoefficients[0]);
            sl.setScale(slCoefficients[1]);
            fSL = slOptimum.getValue();

        }

    }

}

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