assertThat(TWO_VALUES_STATS.mean()).isWithin(ALLOWED_ERROR).of(TWO_VALUES_MEAN);
    // For datasets of many double values created from an array, we test many combinations of finite
    // and non-finite values:
    for (ManyValues values : ALL_MANY_VALUES) {
      double mean = Stats.of(values.asArray()).mean();
      if (values.hasAnyNaN()) {
        assertWithMessage("mean of " + values).that(mean).isNaN();

        .isWithin(ALLOWED_ERROR)
        .of(MANY_VALUES_SUM_OF_PRODUCTS_OF_DELTAS / MANY_VALUES_COUNT);
    // For datasets of many double values, we test many combinations of finite and non-finite
    // x-values:
    for (ManyValues values : ALL_MANY_VALUES) {
      PairedStatsAccumulator accumulator =
          createFilledPairedStatsAccumulator(values.asIterable(), OTHER_MANY_VALUES);

   *   computeInPlace;
   * - (except that, for non-finite values, we don't do all combinations exhaustively);
   * - percentiles with index and with indexes taking int-varargs, and with compute taking a
   *   double-collection and with computeInPlace.
   */

  private static final double ALLOWED_ERROR = 1.0e-10;

  /**
   * A {@link Correspondence} which accepts finite values within {@link #ALLOWED_ERROR} of each
   * other.
   */

    assertThat(TWO_VALUES_PAIRED_STATS.populationCovariance())
        .isWithin(ALLOWED_ERROR)
        .of(TWO_VALUES_SUM_OF_PRODUCTS_OF_DELTAS / 2);
    // For datasets of many double values, we test many combinations of finite and non-finite
    // x-values:
    for (ManyValues values : ALL_MANY_VALUES) {
      PairedStats stats = createPairedStatsOf(values.asIterable(), OTHER_MANY_VALUES);
      double populationCovariance = stats.populationCovariance();

  /**
   * Helper class for testing with non-finite values. {@link #ALL_MANY_VALUES} gives a number of
   * instances with many combinations of finite and non-finite values. All have {@link
   * #MANY_VALUES_COUNT} values. If all the values are finite then the mean is {@link
   * #MANY_VALUES_MEAN} and the sum-of-squares-of-deltas is {@link
   * #MANY_VALUES_SUM_OF_SQUARES_OF_DELTAS}. The smallest and largest finite values are always

        .isWithin(ALLOWED_ERROR)
        .of(MANY_VALUES_MEAN);
    // For datasets of many double values created from an iterable, we test many combinations of
    // finite and non-finite values:
    for (ManyValues values : ALL_MANY_VALUES) {
      StatsAccumulator accumulator = new StatsAccumulator();
      StatsAccumulator accumulatorByAddAllStats = new StatsAccumulator();

  private enum TimeoutsToUse {
    ANY(Timeout.values()),
    PAST(Timeout.MIN, Timeout.MINUS_SMALL, Timeout.ZERO),
    FUTURE(Timeout.SMALL, Timeout.MAX),
    SMALL(Timeout.SMALL),
    FINITE(Timeout.MIN, Timeout.MINUS_SMALL, Timeout.ZERO, Timeout.SMALL),
    INFINITE(Timeout.LARGE, Timeout.MAX);

    final ImmutableList<Timeout> timeouts;

    TimeoutsToUse(Timeout... timeouts) {

    } catch (UnsupportedOperationException expected) {
    }
  }

  /**
   * Verifies that an Iterator is unmodifiable.
   *
   * <p>This test only works with iterators that iterate over a finite set.
   */
  public static void assertIteratorIsUnmodifiable(Iterator<?> iterator) {
    while (iterator.hasNext()) {
      iterator.next();
      try {
        iterator.remove();