plfit/plfit.py
def discrete_max_likelihood(data, xmin, alpharange=(1.5,3.5), n_alpha=201):
    """
    Returns the *argument* of the max of the likelihood of the data given an input xmin
    """
    likelihoods = discrete_likelihood_vector(data, xmin, alpharange=alpharange, n_alpha=n_alpha)
    Lmax = np.max(likelihoods)
    return Lmax
def discrete_max_likelihood(data, xmin, alpharange=(1.5,3.5), n_alpha=201):
    """
    Returns the *argument* of the max of the likelihood of the data given an input xmin
    """
    likelihoods = discrete_likelihood_vector(data, xmin, alpharange=alpharange, n_alpha=n_alpha)
    Lmax = np.max(likelihoods)
    return Lmax
def discrete_max_likelihood ( data , xmin , alpharange = ( 1.5 , 3.5 ) , n_alpha = 201 ) : likelihoods = discrete_likelihood_vector ( data , xmin , alpharange = alpharange , n_alpha = n_alpha ) Lmax = np . max ( likelihoods ) return Lmax
Returns the *argument* of the max of the likelihood of the data given an input xmin
Returns the * argument * of the max of the likelihood of the data given an input xmin