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A collection of methods to determine the required sample size for the evaluation of inequality constrained hypotheses by means of a Bayes factor. Alternatively, for a given sample size, the unconditional error probabilities or the expected conditional error probabilities can be determined. Additional material on the methods in this package is available in Klaassen, F., Hoijtink, H. & Gu, X. (2019) <doi:10.31219/osf.io/d5kf3>.
| Version: | 0.2.3 |
| Suggests: | knitr, rmarkdown, testthat |
| Published: | 2020-06-22 |
| Author: | Fayette Klaassen |
| Maintainer: | Fayette Klaassen <klaassen.fayette at gmail.com> |
| License: | LGPL-3 |
| NeedsCompilation: | no |
| Materials: | NEWS |
| CRAN checks: | BayesianPower results |
| Reference manual: | BayesianPower.pdf |
| Vignettes: |
BayesianPower |
| Package source: | BayesianPower_0.2.3.tar.gz |
| Windows binaries: | r-devel: BayesianPower_0.2.3.zip, r-release: BayesianPower_0.2.3.zip, r-oldrel: BayesianPower_0.2.3.zip |
| macOS binaries: | r-release (arm64): BayesianPower_0.2.3.tgz, r-oldrel (arm64): BayesianPower_0.2.3.tgz, r-release (x86_64): BayesianPower_0.2.3.tgz, r-oldrel (x86_64): BayesianPower_0.2.3.tgz |
| Old sources: | BayesianPower archive |
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These binaries (installable software) and packages are in development.
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