Package: BayesDIP 0.1.1
BayesDIP: Bayesian Decreasingly Informative Priors for Early Termination Phase II Trials
Provide early termination phase II trial designs with a decreasingly informative prior (DIP) or a regular Bayesian prior chosen by the user. The program can determine the minimum planned sample size necessary to achieve the user-specified admissible designs. The program can also perform power and expected sample size calculations for the tests in early termination Phase II trials. See Wang C and Sabo RT (2022) <doi:10.18203/2349-3259.ijct20221110>; Sabo RT (2014) <doi:10.1080/10543406.2014.888441>.
Authors:
BayesDIP_0.1.1.tar.gz
BayesDIP_0.1.1.zip(r-4.7)BayesDIP_0.1.1.zip(r-4.6)BayesDIP_0.1.1.zip(r-4.5)
BayesDIP_0.1.1.tgz(r-4.6-any)BayesDIP_0.1.1.tgz(r-4.5-any)
BayesDIP_0.1.1.tar.gz(r-4.7-any)BayesDIP_0.1.1.tar.gz(r-4.6-any)
BayesDIP_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
BayesDIP/json (API)
NEWS
| # Install 'BayesDIP' in R: |
| install.packages('BayesDIP', repos = c('https://chenw10.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/chenw10/bayesdip/issues
Last updated from:fa91ebb189. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 146 | ||
| source / vignettes | OK | 160 | ||
| linux-release-x86_64 | OK | 99 | ||
| macos-release-arm64 | OK | 160 | ||
| macos-oldrel-arm64 | OK | 152 | ||
| windows-devel | OK | 73 | ||
| windows-release | OK | 92 | ||
| windows-oldrel | OK | 114 | ||
| wasm-release | OK | 79 |
Exports:OneSampleBernoulliOneSampleBernoulli.DesignOneSampleNormal1OneSampleNormal1.DesignOneSampleNormal2OneSampleNormal2.DesignOneSamplePoissonOneSamplePoisson.DesignTwoSampleBernoulliTwoSampleBernoulli.Design
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| One sample Bernoulli model | OneSampleBernoulli |
| One sample Bernoulli model - Trial Design | OneSampleBernoulli.Design |
| One sample Normal model with one-parameter unknown, given variance | OneSampleNormal1 |
| One sample Normal model with one-parameter unknown, given variance | OneSampleNormal1.Design |
| One sample Normal model with two-parameter unknown - both mean and variance unknown | OneSampleNormal2 |
| One sample Normal model with two-parameter unknown - both mean and variance unknown | OneSampleNormal2.Design |
| One sample Poisson model | OneSamplePoisson |
| One sample Poisson model - Trial Design | OneSamplePoisson.Design |
| Two sample Bernoulli model | TwoSampleBernoulli |
| Two sample Bernoulli model - Trial Design | TwoSampleBernoulli.Design |
