*
   * <p>This fit minimizes the root-mean-square error in {@code y} as a function of {@code x}. This
   * error is defined as the square root of the mean of the squares of the differences between the
   * actual {@code y} values of the data and the values predicted by the fit for the {@code x}
   * values (i.e. it is the square root of the mean of the squares of the vertical distances between

   *
   * <p>This fit minimizes the root-mean-square error in {@code y} as a function of {@code x}. This
   * error is defined as the square root of the mean of the squares of the differences between the
   * actual {@code y} values of the data and the values predicted by the fit for the {@code x}
   * values (i.e. it is the square root of the mean of the squares of the vertical distances between

   *
   * <p>This fit minimizes the root-mean-square error in {@code y} as a function of {@code x}. This
   * error is defined as the square root of the mean of the squares of the differences between the
   * actual {@code y} values of the data and the values predicted by the fit for the {@code x}
   * values (i.e. it is the square root of the mean of the squares of the vertical distances between

   *
   * <p>This fit minimizes the root-mean-square error in {@code y} as a function of {@code x}. This
   * error is defined as the square root of the mean of the squares of the differences between the
   * actual {@code y} values of the data and the values predicted by the fit for the {@code x}
   * values (i.e. it is the square root of the mean of the squares of the vertical distances between

import (
	"fmt"
	. "iter"
	"runtime"
	"testing"
)

func count(n int) Seq[int] {
	return func(yield func(int) bool) {
		for i := range n {
			if !yield(i) {
				break
			}
		}
	}
}

func squares(n int) Seq2[int, int64] {
	return func(yield func(int, int64) bool) {
		for i := range n {
			if !yield(i, int64(i)*int64(i)) {
				break
			}
		}
	}
}

func TestPull(t *testing.T) {

		case *Link:
			p.oneLongLine(out, t.Text)
		case *DocLink:
			p.oneLongLine(out, t.Text)
		}
	}
}

// wrap wraps words into lines of at most max runes,
// minimizing the sum of the squares of the leftover lengths
// at the end of each line (except the last, of course),
// with a preference for ending lines at punctuation (.,:;).
//
// The returned slice gives the indexes of the first words

   * 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
   * {@link #MANY_VALUES_MIN} and {@link #MANY_VALUES_MAX}, although setting non-finite values will

		for w != 0 {
			i--
			s[i] = digits[w&mask]
			w >>= shift
		}

	} else {
		bb, ndigits := maxPow(b)

		// construct table of successive squares of bb*leafSize to use in subdivisions
		// result (table != nil) <=> (len(x) > leafSize > 0)
		table := divisors(len(x), b, ndigits, bb)

		// preserve x, create local copy for use by convertWords
		q := nat(nil).set(x)

func basicSqr(z, x nat) {
	n := len(x)
	tp := getNat(2 * n)
	t := *tp // temporary variable to hold the products
	clear(t)
	z[1], z[0] = mulWW(x[0], x[0]) // the initial square
	for i := 1; i < n; i++ {
		d := x[i]
		// z collects the squares x[i] * x[i]
		z[2*i+1], z[2*i] = mulWW(d, d)
		// t collects the products x[i] * x[j] where j < i
		t[2*i] = addMulVVW(t[i:2*i], x[0:i], d)
	}

            }
          },
          "is identical to or " + FINITE_QUANTILE_CORRESPONDENCE);

  // 1. Tests on a hardcoded dataset for chains starting with median(), quartiles(), and scale(10):

  /** The squares of the 16 integers from 0 to 15, in an arbitrary order. */
  private static final ImmutableList<Double> SIXTEEN_SQUARES_DOUBLES =
      ImmutableList.of(