validate_input_column

Validates the input column exists in the dataframe, is of the correct type,
and that all values are greater than or equal to 0.

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

validate_input_column function

<dl><dt>column_name</dt>
<dd>String value of the column name</dd>
<dt>input_df</dt>
<dd>Dataframe containing option_name (str) and various other columns
depending on the distribution type. See vignette for more details.</dd>
<dt>greater_than_zero</dt>
<dd>Boolean: Do all values in the column have to be greater than zero?</dd></dl>

Arguments

Validate Input Column — validate_input_column

<dl>

<dt>column_name</dt>
<dd>String value of the column name</dd>


<dt>input_df</dt>
<dd>Dataframe containing option_name (str) and various other columns
depending on the distribution type. See vignette for more details.</dd>


<dt>greater_than_zero</dt>
<dd>Boolean: Do all values in the column have to be greater than zero?</dd>

</dl>

validate_input_column: Validate Input Column

Description

Usage

Value

Arguments