Java Code Examples for org.apache.commons.math3.stat.descriptive.moment.Variance#evaluate()

The following examples show how to use org.apache.commons.math3.stat.descriptive.moment.Variance#evaluate() . You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may check out the related API usage on the sidebar.

Example 1

Source File: TestDoubleVariancePopAggregation.java From presto with Apache License 2.0

5 votes

@Override
protected Number getExpectedValue(int start, int length)
{
    if (length == 0) {
        return null;
    }

    double[] values = new double[length];
    for (int i = 0; i < length; i++) {
        values[i] = start + i;
    }

    Variance variance = new Variance(false);
    return variance.evaluate(values);
}

Example 2

Source File: TestLongVariancePopAggregation.java From presto with Apache License 2.0

5 votes

@Override
protected Number getExpectedValue(int start, int length)
{
    if (length == 0) {
        return null;
    }

    double[] values = new double[length];
    for (int i = 0; i < length; i++) {
        values[i] = start + i;
    }

    Variance variance = new Variance(false);
    return variance.evaluate(values);
}

Example 3

Source File: TestDoubleVarianceAggregation.java From presto with Apache License 2.0

5 votes

@Override
protected Number getExpectedValue(int start, int length)
{
    if (length < 2) {
        return null;
    }

    double[] values = new double[length];
    for (int i = 0; i < length; i++) {
        values[i] = start + i;
    }

    Variance variance = new Variance();
    return variance.evaluate(values);
}

Example 4

Source File: TestLongVarianceAggregation.java From presto with Apache License 2.0

5 votes

@Override
protected Number getExpectedValue(int start, int length)
{
    if (length < 2) {
        return null;
    }

    double[] values = new double[length];
    for (int i = 0; i < length; i++) {
        values[i] = start + i;
    }

    Variance variance = new Variance();
    return variance.evaluate(values);
}

Example 5

Source File: CorrelationExample.java From Java-Data-Analysis with MIT License

5 votes

static double rho(double[][] data) {
    Variance v = new Variance();
    double varX = v.evaluate(data[0]);
    double sigX = Math.sqrt(varX);
    double varY = v.evaluate(data[1]);
    double sigY = Math.sqrt(varY);
    Covariance c = new Covariance(data);
    double sigXY = c.covariance(data[0], data[1]);
    return sigXY/(sigX*sigY);
}

Example 6

Source File: RandomInitHMM.java From HMMRATAC with GNU General Public License v3.0

4 votes

private List<OpdfMultiGaussian> setVectorPDF(ArrayList<ObservationVector> obs){
	List<OpdfMultiGaussian> opdf = new ArrayList<OpdfMultiGaussian>();
	ObservationVector o = obs.get(0);
	int dim = o.dimension();
	double[] means = new double[dim];
	Mean mu = new Mean();
	Variance v = new Variance();
	double[] vars = new double[dim];
	double[] vals = new double[obs.size()];
	for (int i = 0;i < dim;i++){
		
		for (int a = 0;a < obs.size();a++){
			vals[a] = obs.get(a).value(i);
		}
		means[i] = mu.evaluate(vals, 0, vals.length);
		vars[i] = v.evaluate(vals);
	}
	double[][] Means = new double[numStates][dim];
	double[][] Vars = new double[numStates][dim];
	for (int i = 0; i < means.length;i++){
		double mean = means[i];
		double var = vars[i];
		
		double sd = Math.sqrt(var);
		double meanLower = mean - (3.0*sd);
		double meanUpper = mean + (3.0*sd);
		double varLower = 0.5 * var;
		double varUpper = 3 * var;
		
		
		double meanStep = (meanUpper - meanLower) / ((double)numStates - 1);
		double varStep = (varUpper - varLower) / ((double) numStates - 1);
		//System.out.println((meanUpper-meanLower)+"\t"+meanStep);
		for(int a = 0;a < numStates;a++){
			Means[a][i] = meanLower + (a * meanStep);
			Vars[a][i] = varLower + (a * varStep);
			//System.out.println(Means[a][i]);
			//System.out.println(Vars[a][i]);
		}
		
	}
	for (int i = 0;i < Means.length;i++){
		//System.out.println(Means.length);
		double[][] cov = new double[dim][dim];
		for (int a = 0;a < Means[i].length;a++){
			//System.out.println(Means[i].length);
			cov[a][a] = Vars[i][a];
			//System.out.println(cov[a][a]);
		}
		OpdfMultiGaussian pdf = new OpdfMultiGaussian(Means[i],cov);
		opdf.add(pdf);
	}
	
	return opdf;
	
}

Example 7