/** * Calculates the standard deviation of all attribute values. * * @param attributeValues attribute values * @return the standard deviation */ public Double calculateStandardDeviation( Comparable[] attributeValues, Double mean ) { StandardDeviation standardDeviation = new StandardDeviation(); Double evaluatedStdDev = standardDeviation.evaluate( convertToPrimitives( attributeValues ), mean ); log.debug( "standardDeviation( " + mean + " ) = " + evaluatedStdDev ); return evaluatedStdDev; }
/** * {@inheritDoc} */ @Override public StandardDeviation copy() { StandardDeviation result = new StandardDeviation(); copy(this, result); return result; }
/** * Copies source to dest. * <p>Neither source nor dest can be null.</p> * * @param source StandardDeviation to copy * @param dest StandardDeviation to copy to * @throws NullPointerException if either source or dest is null */ public static void copy(StandardDeviation source, StandardDeviation dest) { dest.setData(source.getDataRef()); dest.variance = source.variance.copy(); }
/** * Computes the standard deviation. * * @param meter * the meter of the mean * @return the standard deviation */ public final double getStandardDeviation(final AbstractMeter meter) { checkIfMeterExists(meter); final AbstractUnivariateStatistic stdDev = new StandardDeviation(); final CollectionDoubleCollection doubleColl = new CollectionDoubleCollection(this.meterResults.get(meter)); return stdDev.evaluate(doubleColl.toArray(), 0, doubleColl.toArray().length); }
/** * Copy constructor, creates a new {@code StandardDeviation} identical * to the {@code original} * * @param original the {@code StandardDeviation} instance to copy */ public StandardDeviation(StandardDeviation original) { copy(original, this); }
StandardDeviation std = new StandardDeviation(); double SIGM = std.evaluate(conv, MU);
/** * Copy constructor, creates a new {@code StandardDeviation} identical * to the {@code original} * * @param original the {@code StandardDeviation} instance to copy */ public StandardDeviation(StandardDeviation original) { copy(original, this); }
int k = 0; Mean mean = new Mean(); StandardDeviation stdev = new StandardDeviation(); stdevSize = (float) stdev.evaluate(distribution);
/** * {@inheritDoc} */ @Override public StandardDeviation copy() { StandardDeviation result = new StandardDeviation(); copy(this, result); return result; }
int k = 0; Mean mean = new Mean(); StandardDeviation stdev = new StandardDeviation(); stdevSize = (float) stdev.evaluate(distribution);
double v = (new StandardDeviation()).evaluate(values); value = Double.toString(v); } else {
protected void compute() { Percentile percentile = new Percentile(); double[] rawDataAsArray = clearRawDataAndGetAsArray(); if (null != rawDataAsArray && rawDataAsArray.length != 0) { sampleSize = rawDataAsArray.length; percentile.setData(rawDataAsArray); percentile_99_5 = percentile.evaluate(99.5); percentile_99 = percentile.evaluate(99); percentile_90 = percentile.evaluate(90); median = Math.max(1d, percentile.evaluate(50)); max = StatUtils.max(rawDataAsArray); mean = new Mean().evaluate(rawDataAsArray); stddev = new StandardDeviation().evaluate(rawDataAsArray); } computedData.set(getCopyOfComputedData()); }
StandardDeviation std = new StandardDeviation(); header, String.valueOf(mean.evaluate(dVals) + "\u00B1" + String.valueOf(std.evaluate(dVals))));
StandardDeviation std = new StandardDeviation(); header + foldAveraged, String.valueOf(mean.evaluate(dVals) + "\u00B1" + String.valueOf(std.evaluate(dVals))));
config.getMinGradeLevel(), config.getMaxGradeLevel()); StandardDeviation sd = new StandardDeviation(false); double stddev = sd.evaluate(new double[] { config.getMinGradeLevel(), config.getMaxGradeLevel() }); double dev = 0.0; if (score > config.getMaxGradeLevel()) {
values[i++] = rc.doubleValue(); StandardDeviation stdDev = new StandardDeviation(); Mean mean = new Mean(); double std = stdDev.evaluate(values); double m = mean.evaluate(values); System.out.println("mean: " + m + " std dev: " + std);