[EMAIL PROTECTED] (jennl) wrote in message news:<[EMAIL PROTECTED]>...
> I am first trying to build a model using regression analysis to
> explain weekly sales, stripped of all exogenous variables (pricing,
> seasonality, etc) and all marketing expenditures 


You shouldn't strip or pre-filter these exogenous variables as their
impact or weight is most likely inter-dependent with your three
additional variables. Further more there may be lag effects of these
stage 1 variables that you might not be correctly forming.
Additionally there may be Interventions such as Level Shifts or Local
time trends or Holiday Events which might change the Y variable
before,on or after these events. In addition since you are dealing
with time series there may be autoregressive structure in the errors
reflecting omitted variables and one might need to add an ARIMA
component and/or weekly dummies reflecting a deterministic effect for
the week of the year.

One of our customers Anheuser-Busch (
http://www.autobox.com/stories.html)is using our software (AUTOBOX) to
perform a similar analysis . They are analyzing sales of 50 SKU's at
650,000 retail outlets (stores) by day incorporating
price,weather,holidays,events abd special promotions.

http://www.autobox.com/details.htm report
http://www.autobox.com/actfore.jpg
http://www.autobox.com/intrvent.html
http://www.autobox.com/equation.txt
http://www.autobox.com/verbal.txt
http://www.autobox.com/stat.html

Specifically they include a 0/1 variable for off/on promotion and
price to customer in order to estimate the impact of promotion and the
impact of price.

If you wish to discuss this further please feel free to give me a call
at
215-675-0652

Dave Reilly
Automatic Forecasting Systems
http://www.autobox.com




Regards
.
.
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