@Test public void testCdf() { Random gen = RandomUtils.getRandom(); double offset = 0; double scale = 1; for (int k = 0; k < 20; k++) { Normal dist = new Normal(offset, scale, null); DistributionChecks.checkCdf(offset, scale, dist, breaks, quantiles); offset = gen.nextGaussian(); scale = Math.exp(3 * gen.nextGaussian()); } }
@Override public double cdf(double x) { return Probability.normal(mean, variance, x); }
Normal extends AbstractContinousDistribution { @Override public double cdf(double x) { return Probability.normal(mean, variance, x); } }
Normal extends AbstractContinousDistribution { @Override public double cdf(double x) { return Probability.normal(mean, variance, x); } Normal(double mean, double standardDeviation, Random randomGenerator); }
Normal extends AbstractContinousDistribution { @Override public double cdf(double x) { return Probability.normal(mean, variance, x); } Normal(double mean, double standardDeviation, Random randomGenerator); @Override double cdf(double x); @Override double pdf(double x); @Override double nextDouble(); @Override final void setRandomGenerator(Random randomGenerator); final void setState(double mean, double standardDeviation); @Override String toString(); }
Normal extends AbstractContinousDistribution { @Override public double cdf(double x) { return Probability.normal(mean, variance, x); } Normal(double mean, double standardDeviation, Random randomGenerator); @Override double cdf(double x); @Override double pdf(double x); @Override double nextDouble(); @Override final void setRandomGenerator(Random randomGenerator); final void setState(double mean, double standardDeviation); @Override String toString();  }