Robyn: Semi-Automated Marketing Mix Modeling (MMM) from Meta Marketing Science

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: 3.6.3
Depends: R (≥ 4.0.0)
Imports: data.table, doParallel, doRNG, dplyr, foreach, ggplot2, ggridges, glmnet, lares, lubridate, minpack.lm, nloptr, patchwork, prophet, reticulate, rPref, stringr, tidyr
Suggests: shiny
Published: 2022-05-06
Author: Gufeng Zhou [aut], Leonel Sentana [aut], Igor Skokan [aut], Bernardo Lares [cre, aut], Meta Platforms, Inc. [cph, fnd]
Maintainer: Bernardo Lares <bernardolares at fb.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

Documentation:

Reference manual: Robyn.pdf

Downloads:

Package source: Robyn_3.6.3.tar.gz
Windows binaries: r-devel: Robyn_3.6.3.zip, r-release: Robyn_3.6.3.zip, r-oldrel: Robyn_3.6.3.zip
macOS binaries: r-release (arm64): Robyn_3.6.3.tgz, r-oldrel (arm64): Robyn_3.6.3.tgz, r-release (x86_64): Robyn_3.6.3.tgz, r-oldrel (x86_64): Robyn_3.6.3.tgz

Linking:

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