Retail Predictive Application Server (MOSC)

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Causal Forecast in RDF 14.1

edited Mar 29, 2017 5:00AM in Retail Predictive Application Server (MOSC) 2 commentsAnswered

Hi,

I have a query on how the different Causal Variable Type works while calculating the causal effect. The products are mainly Short Life Cycle items (Baselined using Bayesian method) which are in the middle of their life cycle with a few promo indicators on its own history.

When I kept Automatic for all the items within the subclass ( 20% of products are in season and remaining in history), it gave no effect at all.

When I kept it in Forced In, it calculated the effects but the numbers where not very helpful. There was a causal effect of 0.05 and also there was an effect of 210000.

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