Example usage for org.apache.commons.math.distribution BetaDistributionImpl density

Introduction

In this page you can find the example usage for org.apache.commons.math.distribution BetaDistributionImpl density.

Prototype

@Override
public double density(double x) 

Source Link

Document

Return the probability density for a particular point.

Usage

From source file:change_point_detection.BetaDistributionChangePoint.java

public int/*estimated change point*/ detectChange() throws Exception {
    int estimatedChangePoint = -1;
    int N = this.dynamicWindow.size();
    this.cushion = Math.max(100, (int) Math.floor(Math.pow(N, gamma)));
    //mean conf. should not fall below 0.3
    if (N > (2 * this.cushion) && calculateMean(0, N - 1) <= 0.3)
        return N - 1;
    double threshold = -Math.log(this.sensitivity);

    double w = 0;
    int kAtMaxW = -1;
    for (int k = this.cushion; k <= N - this.cushion; k++) {
        if (calculateMean(k, N - 1) <= 0.95 * calculateMean(0, k - 1)) {
            double skn = 0;
            /* estimate pre and post change parameters */
            double alphaPreChange = calcBetaDistAlpha(0, k - 1);
            double betaPreChange = calculateBetaDistBeta(alphaPreChange, 0, k - 1);
            double alphaPostChange = calcBetaDistAlpha(k, N - 1);
            double betaPostChange = calculateBetaDistBeta(alphaPostChange, k, N - 1);

            BetaDistributionImpl preBetaDist = new BetaDistributionImpl(alphaPreChange, betaPreChange);
            BetaDistributionImpl postBetaDist = new BetaDistributionImpl(alphaPostChange, betaPostChange);

            for (int i = k; i < N; i++) {
                try {
                    skn += Math.log(postBetaDist.density(this.dynamicWindow.get(i).doubleValue())
                            / preBetaDist.density(this.dynamicWindow.get(i).doubleValue()));
                } catch (Exception e) {
                    e.printStackTrace();
                    System.out.println("continuing...");
                    skn = 0;//from   w w  w  .j  av a  2  s .c o m
                    break;
                }
            }
            if (skn > w) {
                w = skn;
                kAtMaxW = k;
            }
        }
    }
    if (w >= threshold && kAtMaxW != -1) {
        System.out.println("\nChangePoint Found!");
        estimatedChangePoint = kAtMaxW;
        System.out.println("Estimated change point is " + estimatedChangePoint);
    }
    //force change point if confidence falls down terribly
    if (estimatedChangePoint == -1 && N >= 100 && calculateMean(0, N - 1) < 0.3)
        estimatedChangePoint = N - 1;
    return estimatedChangePoint;
}

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From source file:change_point_detection.CpdDP.java

public int/*estimated change point*/ detectChange() throws Exception {
    int estimatedChangePoint = -1;
    int N = this.dynamicWindow.size();
    this.cushion = Math.max(100, (int) Math.floor(Math.pow(N, gamma)));
    //mean conf. should not fall below 0.3
    double preChangeMean, postChangeMean, wholeMean;
    wholeMean = calculateMean(0, N - 1);
    if ((N > (2 * this.cushion) && wholeMean <= 0.3) || this.dynamicWindow.size() > this.dim)
        return N - 1;
    double threshold = -Math.log(this.sensitivity);
    double w = 0;
    int kAtMaxW = -1;
    for (int k = this.cushion; k <= N - this.cushion; k++) {
        double skn = 0;
        int prevN = this.trackN[k];
        preChangeMean = prevN == -1 ? calculateMean(0, k - 1)
                : this.cusumElementArr[prevN][k].getPreChangeMean();
        postChangeMean = calculateMean(k, N - 1);
        if (postChangeMean <= (1 - this.secAlgMarSlack) * preChangeMean) {//signal from secondary
            if (prevN == -1) {
                //calculate from scratch
                /* estimate pre and post change parameters */
                double alphaPreChange = calcBetaDistAlpha(0, k - 1, preChangeMean);
                double betaPreChange = calculateBetaDistBeta(alphaPreChange, 0, k - 1, preChangeMean);
                double alphaPostChange = calcBetaDistAlpha(k, N - 1, postChangeMean);
                double betaPostChange = calculateBetaDistBeta(alphaPostChange, k, N - 1, postChangeMean);
                BetaDistributionImpl preBetaDist = new BetaDistributionImpl(alphaPreChange, betaPreChange);
                BetaDistributionImpl postBetaDist = new BetaDistributionImpl(alphaPostChange, betaPostChange);
                for (int i = k; i < N; i++) {
                    try {
                        skn += Math.log(postBetaDist.density(this.dynamicWindow.get(i).doubleValue())
                                / preBetaDist.density(this.dynamicWindow.get(i).doubleValue()));
                    } catch (Exception e) {
                        e.printStackTrace();
                        System.out.println("continuing...");
                        skn = 0;//from   w w w.  j  a v a  2 s .c o  m
                        break;
                    }
                }
                this.cusumElementArr[N - 1][k] = new CusumElement(preBetaDist, postBetaDist, preChangeMean,
                        skn);
            } else {//warning and calculate recursively
                double alphaPostChange2 = calcBetaDistAlpha(k, N - 1, postChangeMean);
                double betaPostChange2 = calculateBetaDistBeta(alphaPostChange2, k, N - 1, postChangeMean);
                BetaDistributionImpl postBetaDist2 = new BetaDistributionImpl(alphaPostChange2,
                        betaPostChange2);
                skn += this.cusumElementArr[prevN][k].getCusumScore();
                for (int i = prevN + 1; i < N; i++) {
                    try {
                        skn += Math.log(postBetaDist2.density(this.dynamicWindow.get(i).doubleValue())
                                / this.cusumElementArr[prevN][k].getPreChangeDist()
                                        .density(this.dynamicWindow.get(i).doubleValue()));
                    } catch (Exception e) {
                        e.printStackTrace();
                        System.out.println("continuing...");
                        skn = 0;
                        break;
                    }
                }
                this.cusumElementArr[N - 1][k] = new CusumElement(
                        this.cusumElementArr[prevN][k].getPreChangeDist(), postBetaDist2, preChangeMean, skn);
            }
            this.trackN[k] = N - 1;
        }
        if (skn > w) {
            w = skn;
            kAtMaxW = k;
        }
    }
    if (w >= threshold && kAtMaxW != -1) {
        System.out.println("\nChangePoint Found!");
        estimatedChangePoint = kAtMaxW;
        System.out.println("Estimated change point is " + estimatedChangePoint + ", detected at point: " + N);
    }
    //force change point if confidence falls down terribly
    if (estimatedChangePoint == -1 && N >= 100 && wholeMean < 0.3)
        estimatedChangePoint = N - 1;
    return estimatedChangePoint;
}

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