Alternatives and similar repositories for CausalMMM

Users that are interested in CausalMMM are comparing it to the libraries listed below

• slavakx / medium_posts
  ☆89Updated 2 years ago
• OscarEngelbrektson / SyntheticControlMethods
  A Python package for causal inference using Synthetic Controls
  ☆191Updated last year
• MasaAsami / pysynthdid
  Synthetic difference in differences for Python
  ☆84Updated last year
• sibylhe / mmm_stan
  Python/STAN Implementation of Multiplicative Marketing Mix Model, with deep dive into Adstock (carry-over effect), ROAS, and mROAS
  ☆388Updated 3 years ago
• DoubleML / doubleml-docs
  Documentation and User Guide for DoubleML - Double Machine Learning in Python & R
  ☆24Updated this week
• microsoft / SparseSC
  Fit Sparse Synthetic Control Models in Python
  ☆87Updated last year
• Mcompetitions / M5-methods
  Data, Benchmarks, and methods submitted to the M5 forecasting competition
  ☆639Updated 2 years ago
• google / tfp-causalimpact
  ☆121Updated last year
• Minyus / causallift
  CausalLift: Python package for causality-based Uplift Modeling in real-world business
  ☆349Updated 2 years ago
• edgeslab / CTL
  A causal tree method (Causal Tree Learn (CTL)) for heterogeneous treatment effects in Python
  ☆67Updated last year
• google / lifetime_value
  ☆362Updated last year
• DoubleML / doubleml-for-py
  DoubleML - Double Machine Learning in Python
  ☆661Updated this week
• RobKuebler / mamimo
  A package to compute a marketing mix model.
  ☆71Updated 2 years ago
• slavakx / bayesian_mmm
  Code for the article Modeling Marketing Mix using PyMC3
  ☆27Updated 3 years ago
• google / trimmed_match
  This Python library implements Trimmed Match for analyzing randomized paired geo experiments and also implements Trimmed Match Design for…
  ☆69Updated 2 years ago
• leopoldavezac / BayesianMMM
  (ml) - python implementation of bayesian media mix modelling with shape and carryover effect
  ☆58Updated 3 years ago
• dataandcaffeine / pydata-seattle-2017
  Materials for DataScience.com LTV and Neural Nets Talks at PyData Seattle
  ☆39Updated 8 years ago
• olivierzach / bayesian-marketing-attribution
  Marketing attribution using Bayesian credible sets and regression methods
  ☆15Updated 5 years ago
• david26694 / cluster-experiments
  Power analysis and AB test analysis library
  ☆42Updated last month
• rsyi / pylift
  Uplift modeling and evaluation library. Actively maintained pypi version.
  ☆77Updated last year
• facebookincubator / GeoLift
  GeoLift is an end-to-end geo-experimental methodology based on Synthetic Control Methods used to measure the true incremental effect (Lif…
  ☆213Updated last month
• sdfordham / pysyncon
  A python module for the synthetic control method
  ☆76Updated 5 months ago
• ksecology / FixedEffectModel
  Fixedeffectmodel: panel data modeling in Python
  ☆79Updated 3 years ago
• Ibotta / mr_uplift
  Multiple Response Uplift (or heterogeneous treatment effects) package that builds and evaluates tradeoffs with multiple treatments and mu…
  ☆70Updated 5 months ago
• matteocourthoud / Blog-Posts
  Code and notebooks for my Medium blog posts
  ☆128Updated last year
• timmens / causal-forest
  Implements the Causal Forest algorithm formulated in Athey and Wager (2018).
  ☆69Updated 5 years ago
• StatMixedML / LightGBMLSS
  An extension of LightGBM to probabilistic modelling
  ☆334Updated last month
• facebookexperimental / siMMMulator
  siMMMulator is an open source R-package that helps users to generate simulated data to plug into Marketing Mix Models (MMMs). The package…
  ☆56Updated last year
• wayfair / pylift
  Uplift modeling package.
  ☆375Updated 2 years ago
• nlapier2 / PySensemakr
  Python implementation of the original R sensemakr package: https://github.com/carloscinelli/sensemakr
  ☆52Updated 4 months ago