Our great sponsors
-
hierarchicalforecast
Probabilistic Hierarchical forecasting 👑 with statistical and econometric methods.
-
InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
I also recommend you check Nixtla's libraries, in particular StatsForecast and HierarchicalForecast. They offer a wide selection of forecasting models, and can work with multiple time series. Given that you're working with many products in a warehouse, I think the hierarchical forecast can be very useful, especially for the short time series (the ones that don't seem to have enough time stamps).
I also recommend you check Nixtla's libraries, in particular StatsForecast and HierarchicalForecast. They offer a wide selection of forecasting models, and can work with multiple time series. Given that you're working with many products in a warehouse, I think the hierarchical forecast can be very useful, especially for the short time series (the ones that don't seem to have enough time stamps).
Related posts
- [D] When less is more in the hierarchical forecasting case.
- Show HN: Probabilistic hierarchical forecasting with statistical methods
- Sh: Probabilistic hierarchical forecasting with statistical methods
- Probabilistic and nonnegative methods for hierarchical forecasting in python are now available in Nixtla's HierachicalForecast
- Probabilistic hierarchical reconciliation for time series