rangi513/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>.
Getting started
Browse package contents
Package details |
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| Author | Ryan Angi |
| Maintainer | Ryan Angi <angi.ryan@gmail.com> |
| License | MIT + file LICENSE |
| Version | 1.3.5 |
| URL | https://github.com/rangi513/grizbayr |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
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