def norm_resid(self):
"""
Residuals, normalized to have unit length and unit variance.
Returns
-------
An array wresid/sqrt(scale)
Notes
-----
This method is untested
"""
if not hasattr(self, 'resid'):
raise ValueError('need normalized residuals to estimate standard\
deviation')
return self.wresid * recipr(np.sqrt(self.scale))
def norm_resid(self):
"""
Residuals, normalized to have unit length and unit variance.
Returns
-------
An array wresid/sqrt(scale)
Notes
-----
This method is untested
"""
if not hasattr(self, 'resid'):
raise ValueError('need normalized residuals to estimate standard\
deviation')
return self.wresid * recipr(np.sqrt(self.scale))
def test_recipr(self):
X = np.array([[2,1],[-1,0]])
Y = tools.recipr(X)
assert_almost_equal(Y, np.array([[0.5,1],[0,0]]))
def test_recipr(self):
X = np.array([[2, 1], [-1, 0]])
Y = tools.recipr(X)
assert_almost_equal(Y, np.array([[0.5, 1], [0, 0]]))
