本文整理了Java中org.apache.commons.math3.random.RandomDataGenerator.nextHypergeometric方法的一些代码示例，展示了RandomDataGenerator.nextHypergeometric的具体用法。这些代码示例主要来源于Github/Stackoverflow/Maven等平台，是从一些精选项目中提取出来的代码，具有较强的参考意义，能在一定程度帮忙到你。RandomDataGenerator.nextHypergeometric方法的具体详情如下：
包路径：org.apache.commons.math3.random.RandomDataGenerator
类名称：RandomDataGenerator
方法名：nextHypergeometric

RandomDataGenerator.nextHypergeometric介绍

[英]Generates a random value from the HypergeometricDistribution.
[中]从超几何分布生成随机值。

代码示例

代码示例来源：origin: org.apache.commons/commons-math3

/**
 * Generates a random value from the {@link org.apache.commons.math3.distribution.HypergeometricDistribution Hypergeometric Distribution}.
 * This implementation uses {@link #nextInversionDeviate(IntegerDistribution) inversion}
 * to generate random values.
 *
 * @param populationSize the population size of the Hypergeometric distribution
 * @param numberOfSuccesses number of successes in the population of the Hypergeometric distribution
 * @param sampleSize the sample size of the Hypergeometric distribution
 * @return random value sampled from the Hypergeometric(numberOfSuccesses, sampleSize) distribution
 * @throws NumberIsTooLargeException  if {@code numberOfSuccesses > populationSize},
 * or {@code sampleSize > populationSize}.
 * @throws NotStrictlyPositiveException if {@code populationSize <= 0}.
 * @throws NotPositiveException  if {@code numberOfSuccesses < 0}.
 * @since 2.2
 */
public int nextHypergeometric(int populationSize, int numberOfSuccesses, int sampleSize)
  throws NotPositiveException, NotStrictlyPositiveException, NumberIsTooLargeException {
  return delegate.nextHypergeometric(populationSize, numberOfSuccesses, sampleSize);
}

代码示例来源：origin: geogebra/geogebra

/**
 * Generates a random value from the {@link org.apache.commons.math3.distribution.HypergeometricDistribution Hypergeometric Distribution}.
 * This implementation uses {@link #nextInversionDeviate(IntegerDistribution) inversion}
 * to generate random values.
 *
 * @param populationSize the population size of the Hypergeometric distribution
 * @param numberOfSuccesses number of successes in the population of the Hypergeometric distribution
 * @param sampleSize the sample size of the Hypergeometric distribution
 * @return random value sampled from the Hypergeometric(numberOfSuccesses, sampleSize) distribution
 * @throws NumberIsTooLargeException  if {@code numberOfSuccesses > populationSize},
 * or {@code sampleSize > populationSize}.
 * @throws NotStrictlyPositiveException if {@code populationSize <= 0}.
 * @throws NotPositiveException  if {@code numberOfSuccesses < 0}.
 * @since 2.2
 */
public int nextHypergeometric(int populationSize, int numberOfSuccesses, int sampleSize)
  throws NotPositiveException, NotStrictlyPositiveException, NumberIsTooLargeException {
  return delegate.nextHypergeometric(populationSize, numberOfSuccesses, sampleSize);
}

代码示例来源：origin: io.virtdata/virtdata-lib-realer

/**
 * Generates a random value from the {@link org.apache.commons.math3.distribution.HypergeometricDistribution Hypergeometric Distribution}.
 * This implementation uses {@link #nextInversionDeviate(IntegerDistribution) inversion}
 * to generate random values.
 *
 * @param populationSize the population size of the Hypergeometric distribution
 * @param numberOfSuccesses number of successes in the population of the Hypergeometric distribution
 * @param sampleSize the sample size of the Hypergeometric distribution
 * @return random value sampled from the Hypergeometric(numberOfSuccesses, sampleSize) distribution
 * @throws NumberIsTooLargeException  if {@code numberOfSuccesses > populationSize},
 * or {@code sampleSize > populationSize}.
 * @throws NotStrictlyPositiveException if {@code populationSize <= 0}.
 * @throws NotPositiveException  if {@code numberOfSuccesses < 0}.
 * @since 2.2
 */
public int nextHypergeometric(int populationSize, int numberOfSuccesses, int sampleSize)
  throws NotPositiveException, NotStrictlyPositiveException, NumberIsTooLargeException {
  return delegate.nextHypergeometric(populationSize, numberOfSuccesses, sampleSize);
}