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>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Language: en-US
Materials: README NEWS
CRAN checks: bayesassurance results


Reference manual: bayesassurance.pdf
Vignettes: Vignette_1


Package source: bayesassurance_0.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
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


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