grizbayr: Bayesian Inference for A|B and Bandit Marketing Tests

Uses simple Bayesian conjugate prior update rules to calculate the win probability of each option, value remaining in the test, and percent lift over the baseline for various marketing objectives. References: Fink, Daniel (1997) "A Compendium of Conjugate Priors" <https://www.johndcook.com/CompendiumOfConjugatePriors.pdf>. Stucchio, Chris (2015) "Bayesian A/B Testing at VWO" <https://vwo.com/downloads/VWO_SmartStats_technical_whitepaper.pdf>.

Version:	1.3.5
Depends:	R (≥ 2.10)
Imports:	purrr, dplyr, tidyr (≥ 1.0.0), magrittr, tibble, rlang
Suggests:	spelling, knitr, testthat (≥ 2.1.0), rmarkdown
Published:	2023-10-09
DOI:	10.32614/CRAN.package.grizbayr
Author:	Ryan Angi
Maintainer:	Ryan Angi <angi.ryan at gmail.com>
BugReports:	https://github.com/rangi513/grizbayr/issues
License:	MIT + file LICENSE
URL:	https://github.com/rangi513/grizbayr
NeedsCompilation:	no
Language:	en-US
Materials:	README NEWS
CRAN checks:	grizbayr results

Documentation:

Reference manual:	grizbayr.pdf
Vignettes:	start

Downloads:

Package source:	grizbayr_1.3.5.tar.gz
Windows binaries:	r-devel: grizbayr_1.3.5.zip, r-release: grizbayr_1.3.5.zip, r-oldrel: grizbayr_1.3.5.zip
macOS binaries:	r-release (arm64): grizbayr_1.3.5.tgz, r-oldrel (arm64): grizbayr_1.3.5.tgz, r-release (x86_64): grizbayr_1.3.5.tgz, r-oldrel (x86_64): grizbayr_1.3.5.tgz
Old sources:	grizbayr archive

Linking:

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