predpove

Predpove is a cross-domain forecasting platform designed to enable the development, evaluation, and deployment of probabilistic forecasts from diverse data sources. It aims to provide a modular workflow for time-series modeling, uncertainty quantification, and scenario analysis, with applicability in meteorology, energy planning, finance, and public health.

The platform supports data ingestion from traditional databases, flat files, and streaming feeds; a modeling engine that includes Bayesian methods, ensemble approaches, and machine learning; backtesting and cross-validation; probabilistic scoring; and visualization and API tools for integration and dissemination of results.

Predpove originated as an international collaboration among researchers and practitioners in the 2010s, with the first public release in 2016 and ongoing development through community contributions. It is described as open-source and community-driven, emphasizing reproducibility and interoperability with other data-science tools.

Users include academic institutions, government agencies, and private organizations that rely on forecast information for planning and risk assessment. Typical workflows cover data preparation, model selection, forecast generation, performance evaluation, and communication of results with explicit uncertainty bounds.

Supporters praise Predpove for flexibility and transparency, while critics point to a learning curve and computational demands for large ensembles. The project continues to evolve with new models, data connectors, and deployment options. See also time-series forecasting, probabilistic programming, ensemble forecasting, backtesting.