* population, this is an estimator of the population standard deviation of the population which
   * is less biased than {@link #populationStandardDeviation()} (the unbiased estimator depends on
   * the distribution). The count must be greater than one.
   *
   * <p>This is not guaranteed to return zero when the dataset consists of the same value multiple

 * described by <a
 * href="http://en.wikipedia.org/wiki/Quantile#Estimating_the_quantiles_of_a_population">
 * wikipedia</a> as providing "Linear interpolation of the modes for the order statistics for the
 * uniform distribution on [0,1]."
 *
 * <h3>Handling of non-finite values</h3>
 *
 * <p>If any values in the input are {@link Double#NaN NaN} then all values returned are {@link

 * constant time operations. Expected in the hashtable sense (depends on the hash function doing a
 * good job of distributing the elements to the buckets to a distribution not far from uniform), and
 * amortized since some operations can trigger a hash table resize.
 *
 * <p>Unlike {@code java.util.HashSet}, iteration is only proportional to the actual {@code size()},

    // and reduces the false-positive probability.
    static final int MAX_RUN_MULTIPLIER = 13;

    /**
     * Checks the whole hash table for poor hash distribution. Takes O(n) in the worst case, O(n /
     * log n) on average.
     *
     * <p>The online hash flooding detecting in RegularSetBuilderImpl.add can detect e.g. many

/**
 * Utilities for benchmarks.
 *
 * <p>In many cases, we wish to vary the order of magnitude of the input as much as we want to vary
 * the input itself, so most methods which generate values use an exponential distribution varying
 * the order of magnitude of the generated values uniformly at random.
 *
 * @author Louis Wasserman
 */
final class MathBenchmarking {
  static final int ARRAY_SIZE = 0x10000;

 * the components to explicitly register with one another (and thus be aware of each other). It is
 * designed exclusively to replace traditional Java in-process event distribution using explicit
 * registration. It is not a general-purpose publish-subscribe system, nor is it intended
 * for interprocess communication.
 *
 * <h2>Receiving Events</h2>
 *

   * population, this is an estimator of the population standard deviation of the population which
   * is less biased than {@link #populationStandardDeviation()} (the unbiased estimator depends on
   * the distribution). The count must be greater than one.
   *
   * <p>This is not guaranteed to return zero when the dataset consists of the same value multiple

    double req = requests.get();
    double hit = req - misses.get();

    // Currently, this is going into /dev/null, but I'll fix that
    System.out.println("hit rate: " + hit / req);
  }

  // for proper distributions later:
  // import JSci.maths.statistics.ProbabilityDistribution;
  // int key = (int) dist.inverse(random.nextDouble());

 * amortized) constant time operations. Expected in the hashtable sense (depends on the hash
 * function doing a good job of distributing the elements to the buckets to a distribution not far
 * from uniform), and amortized since some operations can trigger a hash table resize.
 *
 * <p>Unlike {@code java.util.HashMap}, iteration is only proportional to the actual {@code size()},

 *
 * <p>Registering a DeadEvent subscriber is useful for debugging or logging, as it can detect
 * misconfigurations in a system's event distribution.
 *
 * @author Cliff Biffle
 * @since 10.0
 */
@ElementTypesAreNonnullByDefault
public class DeadEvent {

  private final Object source;
  private final Object event;

  /**