Semi-Automated Marketing Mix Modeling (MMM) aiming to reduce human bias by means of ridge regression and evolutionary algorithms, enables actionable decision making providing a budget allocation and diminishing returns curves and allows ground-truth calibration to account for causation.
| Version: | 3.12.1 |
| Depends: | R (≥ 4.0.0) |
| Imports: | doParallel,doRNG,dplyr,foreach,ggplot2 (≥ 3.4.0),ggridges,glmnet,jsonlite,lares,lubridate,nloptr,patchwork (≥ 1.3.1),prophet,reticulate,stringr,tidyr |
| Published: | 2025-07-02 |
| DOI: | 10.32614/CRAN.package.Robyn |
| Author: | Gufeng Zhou [aut], Bernardo Lares [cre, aut], Igor Skokan [aut], Leonel Sentana [aut], Meta Platforms, Inc. [cph, fnd] |
| Maintainer: | Bernardo Lares <laresbernardo at gmail.com> |
| BugReports: | https://github.com/facebookexperimental/Robyn/issues |
| License: | MIT + fileLICENSE |
| URL: | https://github.com/facebookexperimental/Robyn,https://facebookexperimental.github.io/Robyn/ |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | Robyn results |