src/spectrum/criteria.py
def AICc(N, rho, k, norm=True):
    r"""corrected Akaike information criterion

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


    :validation: double checked versus octave.
    """
    from numpy import log, array
    p = k  #todo check convention. agrees with octave
    res = log(rho) + 2. * (p+1) / (N-p-2)
    return res
def AICc(N, rho, k, norm=True):
    r"""corrected Akaike information criterion

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


    :validation: double checked versus octave.
    """
    from numpy import log, array
    p = k  #todo check convention. agrees with octave
    res = log(rho) + 2. * (p+1) / (N-p-2)
    return res
def AICc ( N , rho , k , norm = True ) : from numpy import log , array p = k #todo check convention. agrees with octave res = log ( rho ) + 2. * ( p + 1 ) / ( N - p - 2 ) return res
r"""corrected Akaike information criterion

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


    :validation: double checked versus octave.
r corrected Akaike information criterion