ELMSO: Implementation of the Efficient Large-Scale Online Display Advertising Algorithm

An implementation of the algorithm described in "Efficient Large- Scale Internet Media Selection Optimization for Online Display Advertising" by Paulson, Luo, and James (Journal of Marketing Research 2018; see URL below for journal text/citation and <http://faculty.marshall.usc.edu/gareth-james/Research/ELMSO.pdf> for a full-text version of the paper). The algorithm here is designed to allocate budget across a set of online advertising opportunities using a coordinate-descent approach, but it can be used in any resource-allocation problem with a matrix of visitation (in the case of the paper, website page- views) and channels (in the paper, websites). The package contains allocation functions both in the presence of bidding, when allocation is dependent on channel-specific cost curves, and when advertising costs are fixed at each channel.

Version: 1.0.1
Depends: R (≥ 3.4.0)
Published: 2020-01-18
Author: Courtney Paulson [aut, cre], Lan Luo [ctb], Gareth James [ctb]
Maintainer: Courtney Paulson <courtneypaulson at suu.edu>
License: GPL-3
URL: <https://journals.sagepub.com/doi/abs/10.1509/jmr.15.0307>
NeedsCompilation: no
CRAN checks: ELMSO results


Reference manual: ELMSO.pdf


Package source: ELMSO_1.0.1.tar.gz
Windows binaries: r-prerel: ELMSO_1.0.1.zip, r-release: ELMSO_1.0.1.zip, r-oldrel: ELMSO_1.0.1.zip
macOS binaries: r-prerel (arm64): ELMSO_1.0.1.tgz, r-release (arm64): ELMSO_1.0.1.tgz, r-oldrel (arm64): ELMSO_1.0.1.tgz, r-prerel (x86_64): ELMSO_1.0.1.tgz, r-release (x86_64): ELMSO_1.0.1.tgz
Old sources: ELMSO archive


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