The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

bayesassurance: Bayesian Assurance Computation

Computes Bayesian assurance under various settings characterized by different assumptions and objectives, including precision-based conditions, credible intervals, and goal functions. All simulation-based functions included in this package rely on a two-stage Bayesian method that assigns two distinct priors to evaluate the probability of observing a positive outcome, which addresses subtle limitations that take place when using the standard single-prior approach. For more information, please refer to Pan and Banerjee (2021) <doi:10.48550/arXiv.2112.03509>.

Version: 0.1.0
Depends: R (≥ 3.5.0)
Imports: ggplot2 (≥ 3.3.5), plotly (≥ 4.10.0), plot3D (≥ 1.4), pbapply (≥ 1.5.0), dplyr (≥ 1.0.8), MASS (≥ 7.3.55), rlang (≥ 1.0.2), stats (≥ 4.0.5), mathjaxr (≥ 1.5.2)
Suggests: rmarkdown, knitr, testthat (≥ 3.0.0)
Published: 2022-06-17
DOI: 10.32614/CRAN.package.bayesassurance
Author: Jane Pan [cre, aut], Sudipto Banerjee [aut]
Maintainer: Jane Pan <jpan1 at ucla.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/jpan928/bayesassurance_rpackage
NeedsCompilation: no
Language: en-US
Materials: README NEWS
CRAN checks: bayesassurance results

Documentation:

Reference manual: bayesassurance.pdf
Vignettes: Vignette_1
Vignette_2
Vignette_3

Downloads:

Package source: bayesassurance_0.1.0.tar.gz
Windows binaries: r-devel: bayesassurance_0.1.0.zip, r-release: bayesassurance_0.1.0.zip, r-oldrel: bayesassurance_0.1.0.zip
macOS binaries: r-release (arm64): bayesassurance_0.1.0.tgz, r-oldrel (arm64): bayesassurance_0.1.0.tgz, r-release (x86_64): bayesassurance_0.1.0.tgz, r-oldrel (x86_64): bayesassurance_0.1.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=bayesassurance to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.