New features:
- Add documentation section on survival analysis and censored data
models
- Add check_test_point method to pm.Model
- Add Ordered Transformation and OrderedLogistic distribution
- Add Chain transformation
- Improve error message Mass matrix contains zeros on the
diagonal. Some derivatives might always be zero during tuning of
pm.sample
- Improve error message NaN occurred in optimization. during ADVI
- Save and load traces without pickle using pm.save_trace and
pm.load_trace
- Add Kumaraswamy distribution
- Add TruncatedNormal distribution
- Rewrite parallel sampling of multiple chains on py3. This resolves
long standing issues when transferring large traces to the main
process, avoids pickling issues on UNIX, and allows us to show a
progress bar for all chains. If parallel sampling is interrupted, we
now return partial results.
- Add sample_prior_predictive which allows for efficient sampling from
the unconditioned model.
- SMC: remove experimental warning, allow sampling using sample,
reduce autocorrelation from final trace.
- Add model_to_graphviz (which uses the optional dependency graphviz)
to plot a directed graph of a PyMC3 model using plate notation.
- Add beta-ELBO variational inference as in beta-VAE model
(Christopher P. Burgess et al. NIPS, 2017)
- Add __dir__ to SingleGroupApproximation to improve autocompletion in
interactive environments
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