plfit/plfit.py
def discrete_max_likelihood_arg(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)
    Largmax = np.argmax(likelihoods)
    return Largmax
def discrete_max_likelihood_arg(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)
    Largmax = np.argmax(likelihoods)
    return Largmax
def discrete_max_likelihood_arg ( data , xmin , alpharange = ( 1.5 , 3.5 ) , n_alpha = 201 ) : likelihoods = discrete_likelihood_vector ( data , xmin , alpharange = alpharange , n_alpha = n_alpha ) Largmax = np . argmax ( likelihoods ) return Largmax
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