Alternatives and similar repositories for tfp-causalimpact

Users that are interested in tfp-causalimpact are comparing it to the libraries listed below

• google / trimmed_match
  This Python library implements Trimmed Match for analyzing randomized paired geo experiments and also implements Trimmed Match Design for…
  ☆70Updated 2 years ago
• jamalsenouci / causalimpact
  Python port of CausalImpact R library
  ☆287Updated last year
• google / matched_markets
  Matched Markets is a Python library for design and analysis of Geo experiments using Matched Markets and Time Based Regression.
  ☆90Updated 4 months ago
• facebookincubator / GeoLift
  GeoLift is an end-to-end geo-experimental methodology based on Synthetic Control Methods used to measure the true incremental effect (Lif…
  ☆204Updated last year
• RobKuebler / mamimo
  A package to compute a marketing mix model.
  ☆70Updated last year
• WillianFuks / tfcausalimpact
  Python Causal Impact Implementation Based on Google's R Package. Built using TensorFlow Probability.
  ☆641Updated 6 months ago
• py-why / causaltune
  AutoML for causal inference.
  ☆224Updated 6 months ago
• larsroemheld / causalinf_ex_elasticity
  A full example for causal inference on real-world retail data, for elasticity estimation
  ☆50Updated 4 years ago
• slavakx / medium_posts
  ☆88Updated 2 years ago
• microsoft / SparseSC
  Fit Sparse Synthetic Control Models in Python
  ☆83Updated last year
• leopoldavezac / BayesianMMM
  (ml) - python implementation of bayesian media mix modelling with shape and carryover effect
  ☆58Updated 3 years ago
• raz1470 / causal_ai
  This project introduces Causal AI and how it can drive business value.
  ☆48Updated 10 months ago
• OscarEngelbrektson / SyntheticControlMethods
  A Python package for causal inference using Synthetic Controls
  ☆185Updated last year
• nlapier2 / PySensemakr
  Python implementation of the original R sensemakr package: https://github.com/carloscinelli/sensemakr
  ☆51Updated last month
• eeghor / mta
  Multi-Touch Attribution
  ☆116Updated 3 years ago
• pymc-labs / pymc-marketing
  Bayesian marketing toolbox in PyMC. Media Mix (MMM), customer lifetime value (CLV), buy-till-you-die (BTYD) models and more.
  ☆891Updated this week
• sibylhe / mmm_stan
  Python/STAN Implementation of Multiplicative Marketing Mix Model, with deep dive into Adstock (carry-over effect), ROAS, and mROAS
  ☆382Updated 3 years ago
• matheusfacure / exploratory-notebooks
  Unstructured Code with interesting analysis
  ☆37Updated 8 months ago
• MasaAsami / pysynthdid
  Synthetic difference in differences for Python
  ☆81Updated last year
• zillow / quantile-forest
  Quantile Regression Forests compatible with scikit-learn.
  ☆233Updated last week
• bookingcom / upliftml
  UpliftML: A Python Package for Scalable Uplift Modeling
  ☆327Updated 2 years ago
• pymc-devs / pymc-bart
  ☆121Updated last week
• DoubleML / doubleml-for-py
  DoubleML - Double Machine Learning in Python
  ☆614Updated last week
• takechanman1228 / mmm_pydata_global_2022
  ☆27Updated 2 years ago
• ColtAllen / btyd
  Buy Till You Die and Customer Lifetime Value statistical models in Python.
  ☆117Updated last year
• lavinei / pybats
  Bayesian time series forecasting and decision analysis
  ☆116Updated 2 years ago
• tcassou / causal_impact
  Python package for causal inference using Bayesian structural time-series models.
  ☆240Updated 4 years ago
• matteocourthoud / Blog-Posts
  Code and notebooks for my Medium blog posts
  ☆127Updated last year
• slavakx / bayesian_mmm
  Code for the article Modeling Marketing Mix using PyMC3
  ☆27Updated 3 years ago
• inovex / justcause
  💊 Comparing causality methods in a fair and just way.
  ☆139Updated 5 years ago