the group wise means were incorrect if models mismatched, recompute always now.

Author: davidsebfischer

batchglm/train/tf/nb_glm/estimator.py

@@ -865,8 +865,7 @@ def __init__(
                         Xdiff = X - np.exp(input_data.design_loc.dot(init_a_xr))
                         variance = np.square(Xdiff).groupby("group").mean(dim="observations")
 
-                        if groupwise_means is None:
-                            groupwise_means = X.groupby("group").mean(dim="observations")
+                        groupwise_means = X.groupby("group").mean(dim="observations")
                         denominator = np.fmax(variance - groupwise_means, 0)
                         denominator = np.nextafter(0, 1, out=denominator.values, where=denominator == 0,
                                                    dtype=denominator.dtype)