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promotionImpact
View on CRAN: Click
here
Download and install promotionImpact package within the R console
Install from CRAN:
install.packages("promotionImpact")
Install from Github:
library("remotes")
install_github("cran/promotionImpact") Install by package version:
library("remotes")
install_version("promotionImpact", "0.1.5") Attach the package and use:
library("promotionImpact")
Maintained by
Nahyun Kim
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-06-05
Latest Update: 2021-04-13
Description:
Analysis and measurement of promotion effectiveness on a given target variable (e.g. daily sales). After converting promotion schedule into dummy or smoothed predictor variables, the package estimates the effects of these variables controlled for trend/periodicity/structural change using prophet by Taylor and Letham (2017) and some prespecified variables (e.g. start of a month).
How to cite:
Nahyun Kim (2019). promotionImpact: Analysis & Measurement of Promotion Effectiveness. R package version 0.1.5, https://cran.r-project.org/web/packages/promotionImpact. Accessed 05 Jun. 2026.
Previous versions and publish date:
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Other R packages that promotionImpact depends,
imports, suggests or enhances
Complete documentation for promotionImpact
Functions, R codes and Examples using
the promotionImpact R package
Some associated functions: compareModels . create.dummy.vars . create.smooth.vars . detectOutliers . format_time . promotion.model . promotionImpact . sim.data . sim.promotion . sim.promotion.sales . value_fit_plot .
Some associated R codes: promotion_impact.R . Full promotionImpact package functions and examples
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