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-any)MOODE_1.1.0.zip(r-4.6-any)MOODE_1.1.0.zip(r-4.5-any)
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✨
DESCRIPTION |NEWS
card.svg |card.png
MOODE/json (API)

# 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 227 downloads 14 exports 9 dependencies

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

TargetResultTimeFilesSyslog
linux-develNOTE91
source / vignettesOK139
linux-releaseNOTE87
macos-releaseNOTE189
macos-oldrelNOTE140
windows-develNOTE70
windows-releaseNOTE61
windows-oldrelNOTE59
wasm-releaseOK85

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

Dependencies:clidigestfarlatticenlmeprogressrrbibutilsRdpackrlang