is_winner_max

Determines if the max or min function should be used for win probability.
If CPA or CPC distribution, lower is better, else higher number is better.

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>.

Ryan Angi

grizbayr

Bayesian Inference for A|B and Bandit Marketing Tests

is_winner_max function

<dl><dt>distribution</dt>
<dd>String: the name of the distribution</dd></dl>

Arguments

Is Winner Max — is_winner_max

<dl>

<dt>distribution</dt>
<dd>String: the name of the distribution</dd>

</dl>

is_winner_max: Is Winner Max

Description

Usage

Value

Arguments