/** * {@inheritDoc} * * For mean parameter {@code k}, the variance is {@code k^2}. */ public double getNumericalVariance() { final double m = getMean(); return m * m; }
/** * {@inheritDoc} * * For mean parameter {@code k}, the mean is {@code k}. */ public double getNumericalMean() { return getMean(); }
/** * {@inheritDoc} * * For mean parameter {@code k}, the mean is {@code k}. */ public double getNumericalMean() { return getMean(); }
/** * {@inheritDoc} * * For mean parameter {@code k}, the variance is {@code k^2}. */ public double getNumericalVariance() { final double m = getMean(); return m * m; }
/** * {@inheritDoc} * * For mean parameter {@code k}, the variance is {@code k^2}. */ public double getNumericalVariance() { final double m = getMean(); return m * m; }
/** * {@inheritDoc} * * For mean parameter {@code k}, the mean is {@code k}. */ public double getNumericalMean() { return getMean(); }
/** * @param param * mean * @return exponential distribution */ protected ExponentialDistribution getExponentialDistribution(double param) { if (exponential == null || exponential.getMean() != param) { exponential = new ExponentialDistribution(1.0 / param); } return exponential; }
@Test public void testRealDistributionDeserializerWithExpDistribution() throws Exception { String syntheticOptions = "{\"seed\":12345," + "\"delayDistribution\":{\"type\":\"exp\",\"mean\":10}}"; SyntheticOptions sourceOptions = optionsFromString(syntheticOptions, SyntheticOptions.class); assertEquals( 10, (long) ((ExponentialDistribution) (sourceOptions.delayDistribution.getDistribution())) .getMean()); }
} else if (c == ExponentialDistribution.class) { ExponentialDistribution ed = (ExponentialDistribution) d; j.writeNumberField("mean", ed.getMean()); } else if (c == FDistribution.class) { FDistribution fd = (FDistribution) d;
} else if (c == ExponentialDistribution.class) { ExponentialDistribution ed = (ExponentialDistribution) d; j.writeNumberField("mean", ed.getMean()); } else if (c == FDistribution.class) { FDistribution fd = (FDistribution) d;