Package · PyPI
PyPI · v1.3.0 · Apache Software License
Marketing Statistical Models in PyMC
Tentative categories were assigned with moderate confidence (0.5 to 0.75): they are shown, but they do not count toward a category’s momentum. How categories work
pip install pymc-marketingPyPI publishes no adoption figure, so there is no growth to derive. Nothing is estimated in its place.
Adoption history
PyPI publishes no adoption count, so there is no history to chart. That is a fact about the registry, not a gap in ours: the package’s releases and maintenance are measured instead.
In the Crest catalog
Bayesian marketing toolbox in PyMC. Media Mix (MMM), customer lifetime value (CLV), buy-till-you-die (BTYD) models and more.
Linked by the package’s own registry metadata.GitHub (opens in a new tab)
<2.0,>=1.2.0<2.0,>=1.2.0<2.0,>=1.2.0>=1.8.1>=3.16.0>=3.5.1<2.5,>=2.0>=2.2<1.0,>=0.20.0>=2.1.0<6.4.0,>=6.3.1<0.16.0,>=0.15.0>=1.1.1>=0.12.2>=2024.11.0>=0.5.1No published news event mentions this package or its repository yet.