lib5c.algorithms.variance.combined module¶
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lib5c.algorithms.variance.combined.
cross_rep_plus_deviation_variance
(obs, exp, rep, model='lognorm', min_disp=1e-08)[source]¶ Estimates pixel-wise variance as the squared deviation between observed and expected values.
Parameters: - obs (dict or list of np.ndarray) – Dict values or list entries are are square, symmetric count matrices across replicates.
- exp (np.ndarray) – Square, symmetric matrix of expected values.
- rep (int or str) – The index into
obs
identifying which replicate to compute variance estimates for. - model ({'lognorm', '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