int actual = LongMath.lessThanBranchFree(x, y);
          assertEquals(expected, actual);
        }
      }
    }
  }

  // Throws an ArithmeticException if "the simple implementation" of binomial coefficients overflows
  @GwtIncompatible // TODO
  private long simpleBinomial(int n, int k) {
    long accum = 1;
    for (int i = 0; i < k; i++) {
      accum = LongMath.checkedMultiply(accum, n - i);
      accum /= i + 1;

reflect the GCM // standard and make binary.BigEndian suitable for marshaling these values, the // bits are stored in big endian order. For example: // // the coefficient of x⁰ can be obtained by v.low >> 63. // the coefficient of x⁶³ can be obtained by v.low & 1. // the coefficient of x⁶⁴ can be obtained by v.high >> 63. // the coefficient of x¹²⁷ can be obtained by v.high & 1. type gcmFieldElement struct { low, high uint64 } // GHASH is exposed to allow crypto/cipher to implement non-AES GCM modes....

reflect the GCM // standard and make binary.BigEndian suitable for marshaling these values, the // bits are stored in big endian order. For example: // // the coefficient of x⁰ can be obtained by v.low >> 63. // the coefficient of x⁶³ can be obtained by v.low & 1. // the coefficient of x⁶⁴ can be obtained by v.high >> 63. // the coefficient of x¹²⁷ can be obtained by v.high & 1. type gcmFieldElement struct { low, high uint64 } // GHASH is exposed to allow crypto/cipher to implement non-AES GCM modes....

        assertWithMessage("Pearson's correlation coefficient of %s", values)
            .that(pearsonsCorrelationCoefficient)
            .isNaN();
        assertWithMessage("Pearson's correlation coefficient by addAll(PairedStats) of %s", values)
            .that(pearsonsCorrelationCoefficient)
            .isNaN();
      } else {
        assertWithMessage("Pearson's correlation coefficient of %s", values)

      if (values.hasAnyNonFinite()) {
        assertWithMessage("Pearson's correlation coefficient of %s", values)
            .that(pearsonsCorrelationCoefficient)
            .isNaN();
      } else {
        assertWithMessage("Pearson's correlation coefficient of %s", values)
            .that(pearsonsCorrelationCoefficient)
            .isWithin(ALLOWED_ERROR)
            .of(

      if (values.hasAnyNonFinite()) {
        assertWithMessage("Pearson's correlation coefficient of %s", values)
            .that(pearsonsCorrelationCoefficient)
            .isNaN();
      } else {
        assertWithMessage("Pearson's correlation coefficient of %s", values)
            .that(pearsonsCorrelationCoefficient)
            .isWithin(ALLOWED_ERROR)
            .of(

    return sumOfProductsOfDeltas / (count() - 1);
  }

  /**
   * Returns the <a href="http://mathworld.wolfram.com/CorrelationCoefficient.html">Pearson's or
   * product-moment correlation coefficient</a> of the values. The count must greater than one, and
   * the {@code x} and {@code y} values must both have non-zero population variance (i.e. {@code

            .size());

    // Almost force an overflow in the binomial coefficient calculation
    assertEquals(
        1391975640 /*C(34,14)*/,
        Collections2.orderedPermutations(concat(nCopies(20, 1), nCopies(14, 2))).size());
    // Do force an overflow in the binomial coefficient calculation
    assertEquals(
        Integer.MAX_VALUE,

            .size());

    // Almost force an overflow in the binomial coefficient calculation
    assertEquals(
        1391975640 /*C(34,14)*/,
        Collections2.orderedPermutations(concat(nCopies(20, 1), nCopies(14, 2))).size());
    // Do force an overflow in the binomial coefficient calculation
    assertEquals(
        Integer.MAX_VALUE,

    return sumOfProductsOfDeltas / (count() - 1);
  }

  /**
   * Returns the <a href="http://mathworld.wolfram.com/CorrelationCoefficient.html">Pearson's or
   * product-moment correlation coefficient</a> of the values. The count must greater than one, and
   * the {@code x} and {@code y} values must both have non-zero population variance (i.e. {@code