I am trying to model gas consumption in France. The industry publishes a formula to use for this. A simplified version looks like this consumption = K * f(x)
, where K
is an adjustment factor, where they try to correct themselves for the error on the model f(x)
. These K
values are published every day.
Using this formula it is simply a matter of plugging the data into f(x)
. However, I dont know what the K
values will be. I have the data for the published K
values for the past 9 years, and they look like this:
Hence I would like to model the K
values, at least for the short term though long term would be useful too.
What is the best way of tackling this problem?
I am thinking ARIMA though I think it may be correlated with weather too.
Useful info:
- The data is auto-correlated
- You can see seasonality in the plot
- The data is stationary
- Suspect correlation with weather
- I have data for a 14 day weather forecast