def probability_peak_exceeds_value(times, peakval):
return (<NUM_LIT:1.0> - peakval)**((times.size - <NUM_LIT>)/<NUM_LIT>)<EOL>
This calculates the probability that periodogram values exceed the given
    peak value.

    This is from page 3 of Zechmeister and Kurster (2009)::

        Prob(p > p_best) = (1 − p_best)**((N−3)/2)

    where::

        p_best is the peak value in consideration
        N is the number of times

    Note that this is for the default normalization of the periodogram,
    e.g. P_normalized = P(omega), such that P represents the sample variance
    (see Table 1).

    Parameters
    ----------

    lspvals : np.array
        The periodogram power value array.

    peakval : float
        A single peak value to calculate the probability for.

    Returns
    -------

    prob: float
        The probability value.