statsmodels.tools.eval_measures.bias¶
- statsmodels.tools.eval_measures.bias(x1, x2, axis=0)[source]¶
bias, mean error
- Parameters:
- x1, x2numpy:array_like
The performance measure depends on the difference between these two arrays.
- axis
int
axis along which the summary statistic is calculated
- Returns:
- bias
ndarray
orfloat
bias, or mean difference along given axis.
- bias
Notes
If
x1
andx2
have different shapes, then they need to broadcast. This usesnumpy.asanyarray
to convert the input. Whether this is the desired result or not depends on the array subclass.