When working with time series data, you might want to determine whether an event has an impact on some response variable or not.
For example, if your company creates an advertisement, you might want to track whether the advertisement results in an increase in sales or not.
That is when causalimpact comes in handy. causalimpact analyses the differences between expected and observed time series data.
With causalimpact, you can infer the expected effect of an intervention in 3 lines of code as shown above.
