AstraZeneca/judgyprophet
Forecasting for knowable future events using Bayesian informative priors (forecasting with judgmental-adjustment).
This tool helps business forecasters incorporate their expert knowledge about upcoming events into sales or demand predictions. You provide your historical sales data and your team's estimates of how future events (like a product launch or price change) will impact those sales. The output is a more accurate forecast that combines statistical modeling with your valuable business insights, specifically designed for those in sales, marketing, or supply chain roles.
No commits in the last 6 months. Available on PyPI.
Use this if your standard statistical forecasts consistently miss the mark because they can't account for the known future events your business anticipates.
Not ideal if you primarily need to forecast without any specific known future events or judgmental adjustments, or if you need robust prediction intervals which are not yet fully implemented.
Stars
58
Forks
2
Language
Python
License
Apache-2.0
Category
Last pushed
Apr 14, 2022
Commits (30d)
0
Dependencies
4
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