Ratio With Shrinkage

Performs empirical bayesian estimation with shrinkage towards a beta prior. Given a dataset with a numerator and a denominator, will calculate the raw ratio as numerator / denom, as well as provide an adjusted ratio that shrinks the ratio towards the observed beta prior.
This is a simplified version that establishes the priors directly from the data given a min_cutoff count of observations.
NOTE: your data should already be aggregated before performing this operation.
Parameters
Name
Type
Description
Is Optional
numerator
column
A column that is pre-aggregated to contain the count of positive cases
​
denom
column
A column that is pre-aggregated to contain the count of ALL cases
​
min_cutoff
int
Enter a minimum value to limit the denominator when creating the prior estimates. Example: if estimating a batter's hitting percentage, entering 500 would limit the estimation of the priors to be only for batters with over 500 at-bats.
​
Example
ds = rasgo.get.dataset(fqtn="BATTING_AVERAGES")
​
ds2 = ds.ratio_with_shrinkage(numerator = 'HITS', 
              denom = 'AT_BATS', 
              min_cutoff = 500)
​
Source Code
https://github.com/rasgointelligence/RasgoTransforms/blob/main/rasgotransforms/rasgotransforms/transforms/ratio_with_shrinkage/snowflake/ratio_with_shrinkage.sql

Name	Type	Description
numerator	column	A column that is pre-aggregated to contain the count of positive cases
denom	column	A column that is pre-aggregated to contain the count of ALL cases
min_cutoff	int	Enter a minimum value to limit the denominator when creating the prior estimates. Example: if estimating a batter's hitting percentage, entering 500 would limit the estimation of the priors to be only for batters with over 500 at-bats.

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Last modified 7mo ago