@Override public ParetoDistribution clone() { return (ParetoDistribution) super.clone(); }
@Override public Double getMean() { return this.getMeanAsDouble(); }
@Override public double sampleAsDouble( final Random random) { return this.sampleAsDoubles(random, 1)[0]; }
@Override public double[] sampleAsDoubles( final Random random, final int count) { final double[] result = new double[count]; this.sampleInto(random, result, 0, count); return result; }
@Override public double[] sampleAsDoubles( final Random random, final int count) { final double[] result = new double[count]; this.sampleInto(random, result, 0, count); return result; }
@Override public CauchyDistribution clone() { CauchyDistribution clone = (CauchyDistribution) super.clone(); return clone; }
@Override public double sampleAsDouble( final Random random) { return this.sampleAsDoubles(random, 1)[0]; }
@Override public double[] sampleAsDoubles( final Random random, final int count) { final double[] result = new double[count]; this.sampleInto(random, result, 0, count); return result; }
@Override public Double getMean() { return this.getMeanAsDouble(); }
@Override public BetaDistribution clone() { return (BetaDistribution) super.clone(); }
@Override public double sampleAsDouble( final Random random) { return this.sampleAsDoubles(random, 1)[0]; }
@Override public Double getMean() { return this.getMeanAsDouble(); }
@Override public UniformDistribution clone() { return (UniformDistribution) super.clone(); }
@Override public void sampleInto( final Random random, final int sampleCount, final Collection<? super Double> output) { final double[] samples = this.sampleAsDoubles(random, sampleCount); for (final double sample : samples) { output.add(sample); } }
@Override public LogisticDistribution clone() { return (LogisticDistribution) super.clone(); }
@Override public void sampleInto( final Random random, final int sampleCount, final Collection<? super Double> output) { final double[] samples = this.sampleAsDoubles(random, sampleCount); for (final double sample : samples) { output.add(sample); } }
@Override public GammaDistribution clone() { return (GammaDistribution) super.clone(); }
@Override public void sampleInto( final Random random, final int sampleCount, final Collection<? super Double> output) { final double[] samples = this.sampleAsDoubles(random, sampleCount); for (final double sample : samples) { output.add(sample); } }
@Override public BetaDistribution clone() { return (BetaDistribution) super.clone(); }
@Override public ChiSquareDistribution clone() { return (ChiSquareDistribution) super.clone(); }