Dear All,
In the time series, if there is an intervention, the modelling of
intervention, one usually uses step function at that time point,
say (0 0 0 0 1 1 1 1 1 1),  then the response series will change the
behavior after this intervention.


However as I am doing drug evaluation project, when a big drug group
off the market, GPs usually will notice it or be informed  about 3-6
months in advance. Then they probably would change their prescriptions
before that drug off the market.  Hence I observed this behavior
change before this intervention.  As there is no response after
intervention, this type of drug is no longer in the market.


Say (0, 0, 1/3, 2/3, 3/3, 1 1 1 1 1), using ramp term like 1/3, 2/3,
3/3 sometimes could capture this.  Using 1/3, 2/3, 3/3, assumes the
change is equally spaced, but it could be not as well.  If it is not,
there is always one point would be detected as an outlier in this ramp
period in the model, but it is not necessary is an outlier as this is
just the response of GP to the information.


Is there anyone knowing about the general modelling approach for such problem?

I may not state quite clear here. If there is any confusion, please
point it out.


Thanks and Regards