lib5c.algorithms.variance.mle module

lib5c.algorithms.variance.mle.mle_variance(obs, exp, model='lognorm', min_obs=2, min_dist=6, regional=False)

Fits a single point estimate of the dispersion across each or all regions under the selected model, and returns the converted variance estimates.

Parameters

• exp (obs,) – The counts dicts of observed and expected data. Keys are region names, values are square, symmetric count matrices.

• model ({'lognorm', 'loglogistic', 'nbinom'}) – The statistical model to use for MLE point estimation.

• min_obs (float) – Fit only points with at least this many observed counts.

• min_dist (int) – Fit only points with at least this interaction distance in bin units.

• regional (bool) – Pass True to fit a separate point estimate for each region.

Returns

The variance estimates.

Return type

dict of np.ndarray