detectOutliers {promotionImpact} | R Documentation |
detect some outliers
Description
detectOutliers
Usage
detectOutliers(
model,
threshold = list(cooks.distance = 1, dfbetas = 1, dffits = 2),
option = 2
)
Arguments
model |
Execution result object : promotionImpact |
threshold |
List of threshold values to be determined as outliers if greater than the written values |
option |
The number of indicators that must be greater than the threshold values to be outliers. |
Details
detectOutliers extracts outliers which affect the average effects of promotions.
Examples
pri1 <- promotionImpact(data=sim.data, promotion=sim.promotion,
time.field = 'dt', target.field = 'simulated_sales',
trend = FALSE, period = NULL, structural.change = FALSE,
logged = TRUE, differencing = TRUE, synergy.promotion = FALSE,
synergy.var = NULL, allow.missing = TRUE)
out <- detectOutliers(model = pri1,
threshold = list(cooks.distance=1, dfbetas=1, dffits=2), option = 1)
[Package promotionImpact version 0.1.5 Index]