arviz.bfmi#

arviz.bfmi(data)[source]#

Calculate the estimated Bayesian fraction of missing information (BFMI).

BFMI quantifies how well momentum resampling matches the marginal energy distribution. For more information on BFMI, see https://arxiv.org/pdf/1604.00695v1.pdf. The current advice is that values smaller than 0.3 indicate poor sampling. However, this threshold is provisional and may change. See pystan_workflow for more information.

Parameters

dataobj: Any object that can be converted to an arviz.InferenceData object. Refer to documentation of arviz.convert_to_dataset() for details. If InferenceData, energy variable needs to be found.

Returns

zarray: The Bayesian fraction of missing information of the model and trace. One element per chain in the trace.

See also

plot_energy: Plot energy transition distribution and marginal energy distribution in HMC algorithms.

Examples

Compute the BFMI of an InferenceData object

In [1]: import arviz as az
   ...: data = az.load_arviz_data('radon')
   ...: az.bfmi(data)
   ...: 
Out[1]: array([0.729448  , 0.67720456, 0.65528958, 0.71930902])

Diagnostics

arviz.ess