Examples with SimpleRegression org.apache.commons.math3.stat.regression.SimpleRegression used on opensource projects

Example 31 with SimpleRegression

use of org.apache.commons.math3.stat.regression.SimpleRegression in project ta4j by ta4j.

the class SimpleLinearRegressionIndicatorTest method calculateLinearRegressionOn4Observations.

@Test
public void calculateLinearRegressionOn4Observations() {
    SimpleLinearRegressionIndicator reg = new SimpleLinearRegressionIndicator(closePrice, 4);
    assertDecimalEquals(reg.getValue(1), 20);
    assertDecimalEquals(reg.getValue(2), 30);
    SimpleRegression origReg = buildSimpleRegression(10, 20, 30, 40);
    assertDecimalEquals(reg.getValue(3), 40);
    assertDecimalEquals(reg.getValue(3), origReg.predict(3));
    origReg = buildSimpleRegression(30, 40, 30, 40);
    assertDecimalEquals(reg.getValue(5), origReg.predict(3));
    origReg = buildSimpleRegression(30, 20, 30, 50);
    assertDecimalEquals(reg.getValue(9), origReg.predict(3));
}

Example 32 with SimpleRegression

use of org.apache.commons.math3.stat.regression.SimpleRegression in project dhis2-core by dhis2.

the class ListGrid method addRegressionColumn.

@Override
public Grid addRegressionColumn(int columnIndex, boolean addHeader) {
    verifyGridState();
    SimpleRegression regression = new SimpleRegression();
    List<Object> column = getColumn(columnIndex);
    int index = 0;
    for (Object value : column) {
        if (value != null && !MathUtils.isEqual(Double.parseDouble(String.valueOf(value)), 0d)) {
            regression.addData(index++, Double.parseDouble(String.valueOf(value)));
        }
    }
    List<Object> regressionColumn = new ArrayList<>();
    for (int i = 0; i < column.size(); i++) {
        final double predicted = regression.predict(i);
        if (!Double.isNaN(predicted)) {
            regressionColumn.add(Precision.round(predicted, 1));
        } else {
            regressionColumn.add(null);
        }
    }
    addColumn(regressionColumn);
    if (addHeader && columnIndex < headers.size()) {
        GridHeader header = headers.get(columnIndex);
        if (header != null) {
            GridHeader regressionHeader = new GridHeader(header.getName() + REGRESSION_SUFFIX, header.getColumn() + REGRESSION_SUFFIX, header.getValueType(), header.isHidden(), header.isMeta());
            addHeader(regressionHeader);
        }
    }
    return this;
}

Example 33 with SimpleRegression

use of org.apache.commons.math3.stat.regression.SimpleRegression in project cloudsim-plus by manoelcampos.

the class Regression method getRobustLoessParameterEstimates.

/**
 * Gets the robust LOESS parameter estimates.
 *
 * @param y the dependent variable
 * @return the robust loess parameter estimates
 */
public static double[] getRobustLoessParameterEstimates(final double... y) {
    final double[] x = createIndependentArray(y.length);
    final SimpleRegression tricubeRegression = newWeightedLinearRegression(x, y, getTricubeWeights(y.length));
    final double[] residuals = new double[y.length];
    for (int i = 0; i < y.length; i++) {
        residuals[i] = y[i] - tricubeRegression.predict(x[i]);
    }
    final SimpleRegression tricubeBySqrRegression = newWeightedLinearRegression(x, y, getTricubeBisquareWeights(residuals));
    final double[] estimates = tricubeBySqrRegression.regress().getParameterEstimates();
    if (Double.isNaN(estimates[0]) || Double.isNaN(estimates[1])) {
        return tricubeRegression.regress().getParameterEstimates();
    }
    return estimates;
}