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