Examples of org.apache.commons.math3.stat.descriptive.rank.PSquarePercentile.PSquareMarkers.estimate()

org.apache.commons.math3.stat.descriptive.rank.PSquarePercentile.PSquareMarkers.estimate()

Helper method to create a multivariate normal mixture model which can be used to initialize {@link #fit(MixtureMultivariateNormalDistribution)}. This method uses the data supplied to the constructor to try to determine a good mixture model at which to start the fit, but it is not guaranteed to supply a model which will find the optimal solution or even converge. @param data Data to estimate distribution @param numComponents Number of components for estimated mixture @return Multivariate normal mixture model estimated from the data @throws NumberIsTooLargeException if {@code numComponents} is greaterthan the number of data rows. @throws NumberIsTooSmallException if {@code numComponents < 2}. @throws NotStrictlyPositiveException if data has less than 2 rows @throws DimensionMismatchException if rows of data have different numbersof columns

                                95.1959, 95.1442, 95.0610, 95.1591, 95.1195,
                                95.1772, 95.0925, 95.1990, 95.1682 }), 0.50);
        for (int i = 0; i < testArray.length; i++) {
            mThat.processDataPoint(testArray[i]);
        }
        mThat.estimate(0);
    }


    @Test(expected = OutOfRangeException.class)
    public void testMarkersWithHigherIndex() {
        PSquareMarkers mThat =

                                95.1959, 95.1442, 95.0610, 95.1591, 95.1195,
                                95.1772, 95.0925, 95.1990, 95.1682 }), 0.50);
        for (int i = 0; i < testArray.length; i++) {
            mThat.processDataPoint(testArray[i]);
        }
        mThat.estimate(6);
    }


    @Test(expected = OutOfRangeException.class)
    public void testMarkerHeightWithLowerIndex() {
        PSquareMarkers mThat =

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