promotionImpact: Analysis & Measurement of Promotion Effectiveness

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: 0.1.2
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), data.table (≥ 1.11.4), ggpubr (≥ 0.1.8), reshape2 (≥ 1.4.3), stringr (≥ 1.3.1), strucchange (≥ 1.5.1), lmtest (≥ 0.9), crayon (≥ 1.3.4), prophet (≥ 0.3.0.1)
Published: 2019-06-05
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

Downloads:

Reference manual: promotionImpact.pdf
Package source: promotionImpact_0.1.2.tar.gz
Windows binaries: r-devel: promotionImpact_0.1.2.zip, r-release: promotionImpact_0.1.2.zip, r-oldrel: promotionImpact_0.1.2.zip
OS X binaries: r-release: promotionImpact_0.1.2.tgz, r-oldrel: promotionImpact_0.1.2.tgz

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