Hallo,
I am currently trying to model the monthly frequency distribution of
electricity consumption (e.g., 20% of the annual consumption takes place in
February) based on explanatory variables such as temperature, oil prices
etc..
I was thinking that an ordered probit model might work with the month being
the dependent variable. The problem is that my dataset includes historic
relative frequencies (e.g., January: 25%, February: 20%, March: 10%, �,
December:10%) rather than individual observations. Can I use a weighting
function such as pweight to take the different frequencies into account? Do
you think another model type might be more suitable?
Thank you very much for your attention and help.
Harald
Harald Scheule, PhD
The RISConsulting Group
420 Boylston Street
Boston, Massachusetts 02116
Phone (617) 867-9010
Fax (617) 867-0025
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