Package: ELMSO 1.0.1

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.

Authors:Courtney Paulson [aut, cre], Lan Luo [ctb], Gareth James [ctb]

ELMSO_1.0.1.tar.gz
ELMSO_1.0.1.zip(r-4.5)ELMSO_1.0.1.zip(r-4.4)ELMSO_1.0.1.zip(r-4.3)
ELMSO_1.0.1.tgz(r-4.4-any)ELMSO_1.0.1.tgz(r-4.3-any)
ELMSO_1.0.1.tar.gz(r-4.5-noble)ELMSO_1.0.1.tar.gz(r-4.4-noble)
ELMSO_1.0.1.tgz(r-4.4-emscripten)ELMSO_1.0.1.tgz(r-4.3-emscripten)
ELMSO.pdf |ELMSO.html
ELMSO/json (API)

# Install 'ELMSO' in R:
install.packages('ELMSO', repos = c('https://cpaulson-suu.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 4 scripts 127 downloads 4 exports 0 dependencies

Last updated 5 years agofrom:427657acd7. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 31 2024
R-4.5-winOKOct 31 2024
R-4.5-linuxOKOct 31 2024
R-4.4-winOKOct 31 2024
R-4.4-macOKOct 31 2024
R-4.3-winOKOct 31 2024
R-4.3-macOKOct 31 2024

Exports:ELMSOELMSO.fixedreach.ELMSOreach.ELMSO.fixed

Dependencies: