'Computes the (beta) coefficients and the bandwidths.
Minimizes ``cv_loo`` with respect to ``b`` and ``bw``.'

def _est_b_bw(self):

    params0 = np.random.uniform(size=((self.k_linear + self.K),))
    b_bw = optimize.fmin(self.cv_loo, params0, disp=0)
    b = b_bw[0:self.k_linear]
    bw = b_bw[self.k_linear:]
    return (b, bw)
