calculate_multi_rev_per_session

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

calculate_multi_rev_per_session function

<dl><dt>conv_rates</dt>
<dd>Dirichlet samples containing a tibble with columns alpha_1, alpha_2, and alpha_0</dd>
<dt>inverse_rev_A</dt>
<dd>Vector of inverse revenue samples from A conversion type</dd>
<dt>inverse_rev_B</dt>
<dd>Vector of inverse revenue samples from B conversion type</dd></dl>

Arguments

Calculate Multi Rev Per Session — calculate_multi_rev_per_session

<dl>

<dt>conv_rates</dt>
<dd>Dirichlet samples containing a tibble with columns alpha_1, alpha_2, and alpha_0</dd>


<dt>inverse_rev_A</dt>
<dd>Vector of inverse revenue samples from A conversion type</dd>


<dt>inverse_rev_B</dt>
<dd>Vector of inverse revenue samples from B conversion type</dd>

</dl>

calculate_multi_rev_per_session: Calculate Multi Rev Per Session

Description

Usage

Value

Arguments