%(super)s

        In addition to data, gives an optional keyword argument k_array
        containing the values to search for k_agg. A brute force search is then
        used to find the parameter k_agg.

def fit_mle(self, data, k_array=np.arange(0.1, 100, 0.1)):
        """%(super)s

        In addition to data, gives an optional keyword argument k_array
        containing the values to search for k_agg. A brute force search is then
        used to find the parameter k_agg.

        """
        # todo: check and mention in docstring biases of mle for k_agg
        data = np.array(data)
        mu = np.mean(data)
        return mu, _solve_k_from_mu(data, k_array, nbinom_nll, mu)