sample_multi_rev_per_session

Adds 5 new nested columns to the input_df: `dirichlet_params`,
 `gamma_params_A`, `gamma_params_B`, and `samples`.
 This samples from multiple revenue per session distributions
 at once.

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

sample_multi_rev_per_session function

<dl><dt>input_df</dt>
<dd>Dataframe containing option_name (str),
sum_conversions (dbl), sum_sessions (dbl), sum_revenue (dbl),
sum_conversion_2 (dbl), sum_sessions_2 (dbl), sum_revenue_2 (dbl).</dd>
<dt>priors</dt>
<dd>Optional list of priors alpha0 and beta0.
Default \(Beta(1,1)\) will be use otherwise.</dd>
<dt>n_samples</dt>
<dd>Optional integer value. Defaults to 50,000 samples.</dd></dl>

Arguments

Sample Multiple Revenue Per Session — sample_multi_rev_per_session

<dl>

<dt>input_df</dt>
<dd>Dataframe containing option_name (str),
sum_conversions (dbl), sum_sessions (dbl), sum_revenue (dbl),
sum_conversion_2 (dbl), sum_sessions_2 (dbl), sum_revenue_2 (dbl).</dd>


<dt>priors</dt>
<dd>Optional list of priors alpha0 and beta0.
Default \(Beta(1,1)\) will be use otherwise.</dd>


<dt>n_samples</dt>
<dd>Optional integer value. Defaults to 50,000 samples.</dd>

</dl>

sample_multi_rev_per_session: Sample Multiple Revenue Per Session

Description

Usage

Value

Arguments

Details