This release kicks off our 2.0 beta release line, which focuses on bringing enhanced parameter estimation and forecasting tools to epymorph. Vignettes will follow soon, but for now the main entry points to the new features are in the epymorph.forecasting.pipeline module: classes ForecastSimulator, ParticleFilterSimulator, and EnsembleKalmanFilterSimulator.
Beta Note
Because this is a beta release line there may be significant changes between now and full release, but we wanted to give you access to these features early. We are currently using this version of epymorph to participate in the CDC FluSight influenza forecasting challenge so we feel confident in the new features.
What's Changed
- Added the ability to create multi-realization forecasts from a model.
- Added an ensemble Kalman filter and an improved particle filter for joint state and parameter estimation.
- Support for missing data.
- Support for more sophisticated relationships between parameters.
- Added the ability to create fitting-to-forecasting pipelines.
- Added ADRIO
CSVFileAxNwhich is particularly useful for loading time-series data with a non-daily period.
Full Changelog: v1.1.0...v2.0.0b0