def AICc(N, rho, k, norm=True):
    'corrected Akaike information criterion\n\n    .. math:: AICc(k) = log(\\rho_k) + 2 \\frac{k+1}{N-k-2}\n\n\n    :validation: double checked versus octave.\n    '
    from numpy import log, array
    p = k
    res = (log(rho) + ((2.0 * (p + 1)) / ((N - p) - 2)))
    return res
corrected Akaike information criterion

.. math:: AICc(k) = log(\rho_k) + 2 \frac{k+1}{N-k-2}


:validation: double checked versus octave.
def AICc(N, rho, k, norm=True):
    'corrected Akaike information criterion\n\n    .. math:: AICc(k) = log(\\rho_k) + 2 \\frac{k+1}{N-k-2}\n\n\n    :validation: double checked versus octave.\n    '
    from numpy import log, array
    p = k
    res = (log(rho) + ((2.0 * (p + 1)) / ((N - p) - 2)))
    return res