Example usage for org.apache.commons.math3.distribution RealDistribution getSupportLowerBound

Introduction

In this page you can find the example usage for org.apache.commons.math3.distribution RealDistribution getSupportLowerBound.

Prototype

double getSupportLowerBound();

Source Link

Document

Access the lower bound of the support.

Usage

From source file:com.wormsim.utils.Utils.java

/**
 * Returns a string representation of the provided distribution. TODO: Make
 * this complete TODO: Make this compatible with custom distributions (or just
 * more complex ones).//  www  .  j a v a  2 s . c o m
 *
 * @param dist The distribution to translate
 *
 * @return The distribution as a string.
 */
public static String realDistributionToString(RealDistribution dist) {
    if (dist instanceof ConstantRealDistribution) {
        return Double.toString(dist.getNumericalMean());
    } else if (dist instanceof UniformRealDistribution) {
        return "Uniform(" + dist.getSupportLowerBound() + "," + dist.getSupportUpperBound() + ")";
    } else if (dist instanceof NormalDistribution) {
        NormalDistribution dist2 = (NormalDistribution) dist;
        return "Normal(" + dist2.getMean() + "," + dist2.getStandardDeviation() + ")";
    } else {
        return dist.toString();
    }
}

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From source file:edu.cmu.tetrad.sem.GeneralizedSemEstimator.java

public GeneralizedSemIm estimate2(GeneralizedSemPm pm, DataSet data) {

    GeneralizedSemIm estIm = new GeneralizedSemIm(pm);
    MyContext context = new MyContext();

    List<Node> nodes = pm.getGraph().getNodes();
    nodes.removeAll(pm.getErrorNodes());

    List<String> parameters = new ArrayList<>(pm.getParameters());

    LikelihoodFittingFunction5 likelihoodFittingFunction = new LikelihoodFittingFunction5(pm, parameters, nodes,
            data, context);//  ww w. j a va 2 s  .co m

    double[] values = new double[parameters.size()];

    for (int j = 0; j < parameters.size(); j++) {
        Expression expression = pm.getParameterEstimationInitializationExpression(parameters.get(j));
        RealDistribution dist = expression.getRealDistribution(context);
        if (dist != null) {
            double lb = dist.getSupportLowerBound();
            double up = dist.getSupportUpperBound();
            values[j] = expression.evaluate(context);
            if (values[j] < lb)
                values[j] = lb;
            if (values[j] > up)
                values[j] = up;
        } else {
            values[j] = expression.evaluate(context);
        }
    }

    double[] point = optimize(likelihoodFittingFunction, values, 1);

    for (int j = 0; j < parameters.size(); j++) {
        estIm.setParameterValue(parameters.get(j), point[j]);
    }

    //        MultiGeneralAndersonDarlingTest test = new MultiGeneralAndersonDarlingTest(allResiduals, allDistributions);
    //        System.out.println("Multi AD A^2 = " + test.getASquared());
    //        System.out.println("Multi AD A^2-Star = " + test.getASquaredStar());
    //        System.out.println("Multi AD p = " + test.getP());

    return estIm;
}

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