Package: OptGS 1.2

OptGS: Near-Optimal Group-Sequential Designs for Continuous Outcomes

Optimal group-sequential designs minimise some function of the expected and maximum sample size whilst controlling the type I error rate and power at a specified level. 'OptGS' provides functions to quickly search for near-optimal group-sequential designs for normally distributed outcomes. The methods used are described in Wason, JMS (2015) <doi:10.18637/jss.v066.i02>.

Authors:James Wason [aut, cre], John Burkardt [ctb], R O'Neill [ctb]

OptGS_1.2.tar.gz
OptGS_1.2.zip(r-4.7)OptGS_1.2.zip(r-4.6)OptGS_1.2.zip(r-4.5)
OptGS_1.2.tgz(r-4.6-x86_64)OptGS_1.2.tgz(r-4.6-arm64)OptGS_1.2.tgz(r-4.5-x86_64)OptGS_1.2.tgz(r-4.5-arm64)
OptGS_1.2.tar.gz(r-4.7-arm64)OptGS_1.2.tar.gz(r-4.7-x86_64)OptGS_1.2.tar.gz(r-4.6-arm64)OptGS_1.2.tar.gz(r-4.6-x86_64)
OptGS_1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
OptGS/json (API)

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

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 5 scripts 611 downloads 2 exports 0 dependencies

Last updated from:bc362fc2a1. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK96
linux-devel-x86_64OK98
source / vignettesOK141
linux-release-arm64OK94
linux-release-x86_64OK105
macos-release-arm64OK158
macos-release-x86_64OK301
macos-oldrel-arm64OK138
macos-oldrel-x86_64OK395
windows-develOK126
windows-releaseOK91
windows-oldrelOK74
wasm-releaseOK78

Exports:optgspowerfamily

Dependencies: