Package: grizbayr 1.3.5

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>.

Authors:Ryan Angi

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Bug tracker:https://github.com/rangi513/grizbayr/issues

On CRAN:

16 exports 10 stars 1.59 score 21 dependencies 3 scripts 296 downloads

Last updated 12 months agofrom:8102c9f759. Checks:OK: 3 NOTE: 4. Indexed: yes.

Exports:estimate_all_valuesestimate_liftestimate_lift_vs_baselineestimate_lossestimate_value_remainingestimate_win_probestimate_win_prob_given_posteriorestimate_win_prob_vs_baselineestimate_win_prob_vs_baseline_given_posteriorfind_best_optionrdirichletsample_from_posteriorupdate_betaupdate_dirichletupdate_gammavalidate_input_df

Dependencies:clicpp11dplyrfansigenericsgluelifecyclemagrittrpillarpkgconfigpurrrR6rlangstringistringrtibbletidyrtidyselectutf8vctrswithr