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User-friendly functions for leveraging (multiple) historical data set(s) for generalized linear models. Contains functions for sampling from the posterior distribution of a generalized linear model using the prior induced by the Bayesian hierarchical model, power prior by Ibrahim and Chen (2000) <doi:10.1214/ss/1009212673>, normalized power prior by Duan et al. (2006) <doi:10.1002/env.752>, normalized asymptotic power prior by Ibrahim et al. (2015) <doi:10.1002/sim.6728>, commensurate prior by Hobbs et al. (2011) <doi:10.1111/j.1541-0420.2011.01564.x>, robust meta-analytic-predictive prior by Schmidli et al. (2014) <doi:10.1111/biom.12242>, and the latent exchangeability prior (LEAP) by Alt et al. (2023) <doi:10.48550/arXiv.2303.05223>. The package compiles all the 'CmdStan' models once during installation using the 'instantiate' package.
Version: | 0.0.3 |
Depends: | R (≥ 4.2.0) |
Imports: | instantiate (≥ 0.1.0), callr, fs, formula.tools, stats, posterior, enrichwith, mclust, bridgesampling |
Suggests: | cmdstanr (≥ 0.6.0), parallel |
Published: | 2024-04-08 |
Author: | Ethan M. Alt [aut, cre, cph], Xinxin Chen [aut], Luiz M. Carvalho [aut], Joseph G. Ibrahim [aut], Xiuya Chang [ctb] |
Maintainer: | Ethan M. Alt <ethanalt at live.unc.edu> |
BugReports: | https://github.com/ethan-alt/hdbayes/issues |
License: | MIT + file LICENSE |
URL: | https://github.com/ethan-alt/hdbayes |
NeedsCompilation: | yes |
SystemRequirements: | CmdStan (https://mc-stan.org/users/interfaces/cmdstan) |
Additional_repositories: | https://mc-stan.org/r-packages/ |
Materials: | NEWS |
CRAN checks: | hdbayes results |
Reference manual: | hdbayes.pdf |
Package source: | hdbayes_0.0.3.tar.gz |
Windows binaries: | r-devel: hdbayes_0.0.3.zip, r-release: hdbayes_0.0.3.zip, r-oldrel: hdbayes_0.0.3.zip |
macOS binaries: | r-release (arm64): hdbayes_0.0.3.tgz, r-oldrel (arm64): hdbayes_0.0.3.tgz, r-release (x86_64): hdbayes_0.0.3.tgz, r-oldrel (x86_64): hdbayes_0.0.3.tgz |
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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.
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