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) <doi:10.7287/peerj.preprints.3190v2> and some prespecified variables (e.g. start of a month).
Version: 0.1.5 Depends: R (≥ 3.5.0), Rcpp (≥ 0.12.17), dplyr (≥ 0.7.6), ggplot2 (≥ 3.0.0), scales (≥ 1.0.0) Imports: KernSmooth (≥ 2.23.15), ggpubr (≥ 0.1.8), reshape2 (≥ 1.4.3), stringr (≥ 1.3.1), strucchange (≥ 1.5.1), lmtest (≥ 0.9), crayon (≥ 1.3.4), prophet (≥ 0.6.1) Published: 2021-04-13 DOI: 10.32614/CRAN.package.promotionImpact Author: Nahyun Kim [cre, aut], Hyemin Um [aut], Eunjo Lee [aut], NCSOFT Corporation [cph] Maintainer: Nahyun Kim <nhkim1302 at ncsoft.com> License: BSD_3_clause + file LICENSE URL: https://github.com/ncsoft/promotionImpact NeedsCompilation: no CRAN checks: promotionImpact results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=promotionImpact to link to this page.
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