lib5c.algorithms.variance.deviation module¶
-
lib5c.algorithms.variance.deviation.
deviation_variance
(obs, exp, model='lognorm', min_disp=1e-08)[source]¶ Estimates pixel-wise variance as the squared deviation between observed and expected values.
- Parameters
exp (obs,) – Square, symmetric matrix of observed and expected values, respectively.
model ({'lognorm', 'nbinom', 'norm'}) – Statistical model to use.
min_disp (float) – Force a minimum value of the dispersion parameter.
- Returns
The first three elements are the mean parameter estimate, dispersion estimate, and variance estimate, respectively, for each pixel. The fourth element is a boolean matrix showing which pixels are considered to be overdispersed.
- Return type
tuple of np.ndarray