Package: RMM 0.1.0

RMM: Revenue Management Modeling

The RMM fits Revenue Management Models using the RDE(Robust Demand Estimation) method introduced in the paper by <doi:10.2139/ssrn.3598259>, one of the customer choice-based Revenue Management Model. Furthermore, it is possible to select a multinomial model as well as a conditional logit model as a model of RDE.

Authors:Chul Kim [aut, cre], Sanghoon Cho [aut], Jongho Im [aut]

RMM_0.1.0.tar.gz
RMM_0.1.0.zip(r-4.7)RMM_0.1.0.zip(r-4.6)RMM_0.1.0.zip(r-4.5)
RMM_0.1.0.tgz(r-4.6-x86_64)RMM_0.1.0.tgz(r-4.6-arm64)RMM_0.1.0.tgz(r-4.5-x86_64)RMM_0.1.0.tgz(r-4.5-arm64)
RMM_0.1.0.tar.gz(r-4.7-arm64)RMM_0.1.0.tar.gz(r-4.7-x86_64)RMM_0.1.0.tar.gz(r-4.6-arm64)RMM_0.1.0.tar.gz(r-4.6-x86_64)
RMM_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
RMM/json (API)

# Install 'RMM' in R:
install.packages('RMM', repos = c('https://statkim7578.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

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

cpp

1.00 score 2 scripts 270 downloads 3 exports 17 dependencies

Last updated from:b17b4f157f. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK181
linux-devel-x86_64OK136
source / vignettesOK168
linux-release-arm64OK132
linux-release-x86_64OK117
macos-release-arm64OK135
macos-release-x86_64OK256
macos-oldrel-arm64OK194
macos-oldrel-x86_64OK268
windows-develOK115
windows-releaseOK107
windows-oldrelOK93
wasm-releaseOK97

Exports:Choice_Setrmmrmm_reshape

Dependencies:clidplyrgenericsgluelifecyclemagrittrnumDerivpillarpkgconfigR6Rcpprlangtibbletidyselectutf8vctrswithr