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:
- data
obj
Any object that can be converted to an
arviz.InferenceData
object. Refer to documentation ofarviz.convert_to_dataset()
for details. If InferenceData, energy variable needs to be found.
- data
- Returns:
- z
array
The Bayesian fraction of missing information of the model and trace. One element per chain in the trace.
- z
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])