Uber Orbit Versions Save

• hot fix on the commit graphs between master and dev

• Hot fix on requirement.txt to set up fix on conda forge as well
• Reduce number of python versions in unit test

Core Changes:

• replace PyStan2 by cmdstanpy (https://github.com/uber/orbit/pull/801)
• update requirement and installation procedures (https://github.com/uber/orbit/commit/073f03fac7c8cecc241909cd20f97124b10ea3f5)
• loggers upgrade

Documentation:

• all tutorial is updated to use cmdstanpy in backend

Core changes:

• add python 3.8 unit tests (https://github.com/uber/orbit/pull/752)
• optimize interface to be compatible with arviz (https://github.com/uber/orbit/pull/755)
• requirements update (https://github.com/uber/orbit/pull/763)
• code clean up (https://github.com/uber/orbit/pull/765)
• dlt global trend prior adjustment (https://github.com/uber/orbit/pull/786)

Documentation:

Tutorial enhancement:

• tutorial refresh (https://github.com/uber/orbit/pull/795)

Utilities:

• uses tqdm in parameters tuning (https://github.com/uber/orbit/pull/762)
• residuals plot (https://github.com/uber/orbit/pull/758)
• simpler stan compile interface (https://github.com/uber/orbit/pull/769)

Core changes:

• Add Conda installation option (#679)
• Suppress the lengthy Stan logging message (#696)
• WBIC for pyro SVI sampling and BIC for MAP optimization (#719, #710)
• Backtest module to include confidence intervals (#724)
• Allow configuration for compiled Stan model path (#713)
• Box plot for regression coefficient comparison (#737)
• Bounded logistic growth for DLT model (#712)
• Enhance regression output reporting (#739)å

Documentation:

• Add blacking linting to Github action workflow (#708)
• Tutorial enhancement

Utilities:

• Add a new method make_future_df to prepare data frame for forecasting (#695)

Core changes:

• Add Conda installation option (#679)
• Suppress the lengthy Stan logging message (#696)
• WBIC for pyro SVI sampling and BIC for MAP optimization (#719, #710)
• Backtest module to include confidence intervals (#724)
• Allow configuration for compiled Stan model path (#713)
• Box plot for regression coefficient comparison (#737)
• Bounded logistic growth for DLT model (#712)
• Enhance regression output reporting (#739)

Documentation:

• Add blacking linting to Github action workflow (#708)
• Tutorial enhancement

Utilities:

• Add a new method make_future_df to prepare data frame for forecasting (#695)

• fix the .mplstyle file path bug

Core changes

• Redesign the model class structure with three core components: model template, estimator, and forecaster (#506, #507, #508, #513)
• Introduce the Kernel-based Time-varying Regression (KTR) model (#515)
• Implement the negative coefficient for LGT and KTR (#600, #601, #609)
• Allow to handle missing values in response for LGT and DLT (#645)
• Implement WBIC value for model candidate selection (#654)

Documentation

• A new series of tutorials for KTR (#558, #559)
• Migrate the CI from TravisCI to Github Actions (#556)
• Missing value handle tutorial (#645)
• WBIC tutorial (#663)

Utilities

• New Plotting Palette (#571, #589)
• Redesign the diagnostic plotting (#581, #607)
• Raise a warning when date index is not evenly distributed (#639)

• Core changes:
  • Use global mean instead of median in ktrx model before next major release

• Core changes
  • Bug fix and code improvement before next major release (#540, #541, #546)
  • lower than matplotlib requirement (#498)