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" <doi:10.1.1.157/5540>. Stucchio, Chris (2015) "Bayesian A/B Testing at VWO" <http://cdn2.hubspot.net/hubfs/310840/VWO_SmartStats_technical_whitepaper.pdf>.

Version: 1.2.1
Depends: R (≥ 2.10)
Imports: purrr, dplyr, tidyr, magrittr, tibble, rlang
Suggests: spelling, knitr, testthat (≥ 2.1.0), rmarkdown
Published: 2020-05-11
Author: Ryan Angi
Maintainer: Ryan Angi <rangi at redventures.com>
License: MIT + file LICENSE
NeedsCompilation: no
Language: en-US
Materials: README
CRAN checks: grizbayr results

Downloads:

Reference manual: grizbayr.pdf
Vignettes: start
Package source: grizbayr_1.2.1.tar.gz
Windows binaries: r-devel: grizbayr_1.2.1.zip, r-release: grizbayr_1.2.1.zip, r-oldrel: grizbayr_1.2.1.zip
macOS binaries: r-release: grizbayr_1.2.1.tgz, r-oldrel: grizbayr_1.2.1.tgz

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