Package: MOODE 1.1.0

Vasiliki Koutra

MOODE: Multi-Objective Optimal Design of Experiments

Provides functionality to generate compound optimal designs for targeting the multiple experimental objectives directly, ensuring that the full set of research questions is answered as economically as possible. Designs can be found using point or coordinate exchange algorithms combining estimation, inference and lack-of-fit criteria that account for model inadequacy. Details and examples are given by Koutra et al. (2024) <doi:10.48550/arXiv.2412.17158>.

Authors:Vasiliki Koutra [aut, cre, cph], Olga Egorova [aut, cph], Steven Gilmour [aut, cph], Luzia Trinca [aut, cph]

MOODE_1.1.0.tar.gz
MOODE_1.1.0.zip(r-4.7)MOODE_1.1.0.zip(r-4.6)MOODE_1.1.0.zip(r-4.5)
MOODE_1.1.0.tgz(r-4.6-any)MOODE_1.1.0.tgz(r-4.5-any)
MOODE_1.1.0.tar.gz(r-4.7-any)MOODE_1.1.0.tar.gz(r-4.6-any)
MOODE_1.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
MOODE/json (API)
NEWS

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

Bug tracker:https://github.com/vkstats/moode/issues

On CRAN:

Conda:

2.70 score 1 scripts 147 downloads 14 exports 9 dependencies

Last updated from:1b6f1dbf4c. Checks:7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64NOTE105
source / vignettesOK149
linux-release-x86_64NOTE101
macos-release-arm64NOTE120
macos-oldrel-arm64NOTE145
windows-develNOTE73
windows-releaseNOTE59
windows-oldrelNOTE75
wasm-releaseOK90

Exports:candidate_set_fullcandidate_set_orthcandidate_trt_setcriteria.GDcriteria.GDPcriteria.GLcriteria.GLPcriteria.mseDcriteria.mseLcriteria.msePcriteria.values.Gcriteria.values.msemoodSearch

Dependencies:clidigestfarlatticenlmeprogressrrbibutilsRdpackrlang