View source: R/pre_processing_data.R
TrimControls | R Documentation |
As the number of controls for a Geo test increases, the model
complexity grows as does the algorithm's run-time. However,
there are diminishing marginal returns in adding too many control
locations, especially if their time-series are very similar.
TrimControls
provides a method to trim the number of controls
in order to reduce run-times with minimal loss of precision. In general,
it is recommended to have 4 to 5 times the number of controls locations
than the ones we have for test locations.
TrimControls(
data,
Y_id = "Y",
time_id = "time",
location_id = "location",
max_controls = 20,
test_locations = c(),
forced_control_locations = c()
)
data |
A data.frame containing the historical conversions by geographic unit. It requires a "locations" column with the geo name, a "Y" column with the outcome data (units), a time column with the indicator of the time period (starting at 1), and covariates. |
Y_id |
Name of the outcome variable (String). |
time_id |
Name of the time variable (String). |
location_id |
Name of the location variable (String). |
max_controls |
Max number of controls, recommended 4x-5x the number of test locations. |
test_locations |
List of test locations. |
forced_control_locations |
List of locations to be forced as controls. |
A data frame with reduced control locations.
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