diff options
Diffstat (limited to 'numpy/lib/polynomial.py')
| -rw-r--r-- | numpy/lib/polynomial.py | 11 |
1 files changed, 6 insertions, 5 deletions
diff --git a/numpy/lib/polynomial.py b/numpy/lib/polynomial.py index 420ec245b..1c124cc0e 100644 --- a/numpy/lib/polynomial.py +++ b/numpy/lib/polynomial.py @@ -494,11 +494,12 @@ def polyfit(x, y, deg, rcond=None, full=False, w=None, cov=False): cov : bool or str, optional If given and not `False`, return not just the estimate but also its covariance matrix. By default, the covariance are scaled by - chi2/sqrt(N-dof), i.e., the weights are presumed to be unreliable - except in a relative sense and everything is scaled such that the - reduced chi2 is unity. This scaling is omitted if ``cov='unscaled'``, - as is relevant for the case that the weights are 1/sigma**2, with - sigma known to be a reliable estimate of the uncertainty. + chi2/dof, where dof = M - (deg + 1), i.e., the weights are presumed + to be unreliable except in a relative sense and everything is scaled + such that the reduced chi2 is unity. This scaling is omitted if + ``cov='unscaled'``, as is relevant for the case that the weights are + 1/sigma**2, with sigma known to be a reliable estimate of the + uncertainty. Returns ------- |