Hi, I'm a bit confused as to what the difference between estimating the trend & seasonal components of a time series and calculating the data adjusted for trend & seasonality. Please could someone clear this up for me?
What do you mean by "calculating the data adjusted for trend and seasonality?" One way to handle seasonality in your regression might be to include indicator (dummy/qualitative/categorical) variables. Thus, having four different seasons S1, S2, S3, S4, we can have a regression Y ~ S2 + S3 + S4 with the usual binary coding (1 if the data point is in that season; 0 otherwise). If you transform your data so that it numerically represents something about seasonality, then the data itself, I'm speculating, would account for the variation such a regression above would try to incorporate. Of course, another way to interpret what you mean by "calculating the data ..." might simply be the coding in a way like I supposed above. I cannot say if I'm answering your question. I'm unclear on your question.