def METHOD_NAME(list1, list2, p, index2word, embedding_space, norm=True):
    """RBO point estimate based on extrapolating observed overlap.
    See equation (32) in paper.
    NOTE: The doctests weren't verified against manual computations but seem
    plausible.
    """
    S, L = sorted((list1, list2), key=len)
    s, l = len(S), len(L)
    x_l = overlap(list1, list2, l, index2word, embedding_space=embedding_space, norm=norm)
    x_s = overlap(list1, list2, s, index2word, embedding_space=embedding_space, norm=norm)
    # the paper says overlap(..., d) / d, but it should be replaced by
    # agreement(..., d) defined as per equation (28) so that ties are handled
    # properly (otherwise values > 1 will be returned)
    # sum1 = sum(p**d * overlap(list1, list2, d)[0] / d for d in range(1, l + 1))
    sum1 = sum(p ** d * agreement(list1, list2, d, index2word=index2word, embedding_space=embedding_space, norm=norm)
               for d in range(1, l + 1))
    sum2 = sum(p ** d * x_s * (d - s) / s / d for d in range(s + 1, l + 1))
    term1 = (1 - p) / p * (sum1 + sum2)
    term2 = p ** l * ((x_l - x_s) / l + x_s / s)
    return term1 + term2