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: |
3.11.1 |
| Depends: |
R (≥ 4.0.0) |
| Imports: |
doParallel, doRNG, dplyr, foreach, ggplot2, ggridges, glmnet, jsonlite, lares, lubridate, minpack.lm, nloptr, patchwork, prophet, reticulate, stringr, tidyr |
| Published: |
2024-06-27 |
| DOI: |
10.32614/CRAN.package.Robyn |
| Author: |
Gufeng Zhou [aut],
Bernardo Lares [cre, aut],
Leonel Sentana [aut],
Igor Skokan [aut],
Meta Platforms, Inc. [cph, fnd] |
| Maintainer: |
Bernardo Lares <laresbernardo at gmail.com> |
| BugReports: |
https://github.com/facebookexperimental/Robyn/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/facebookexperimental/Robyn,
https://facebookexperimental.github.io/Robyn/ |
| NeedsCompilation: |
no |
| Materials: |
README |
| CRAN checks: |
Robyn results |