N = Y_metadata["trials"]
np.testing.assert_array_equal(N.shape, y.shape)
return -y/np.square(inv_link_f) - (N-y)/np.square(1.-inv_link_f)
def d3logpdf_dlink3(self, inv_link_f, y, Y_metadata=None):
After Change
t2 = np.zeros(y.shape)
t1[y>0] = -y[y>0]/np.square(inv_link_f[y>0])
t2[Ny>0] = -(Ny[Ny>0])/np.square(1.-inv_link_f[Ny>0])
return t1+t2
def d3logpdf_dlink3(self, inv_link_f, y, Y_metadata=None):
Third order derivative log-likelihood function at y given inverse link of f w.r.t inverse link of f
