I have 2 time series. 1) monthly residential natural gas demand from 2013 to 2016 2) daily average temperature from 2013 to 31/03/2017
I have to provide a monthly and daily prediction of the residential natural gas demand for the period January 2017 to April 2017.
After having prepared the data handling NaN and Na, I have to transform the temperature in average monthly temperature. Then I should build the model to estimate the future values of the demand.
I am quite new in R and in econometrics.
Which transformation can I use in R to transforme the daily average temperature time series in monthly average temperature time series?
Is vector autocorrelation a good model for seasonal data? I should use the temperature and the old demand values to predict the future demand.
