I'm trying to do time series forecasting with linear regression like it's done in this video: Radial basis forecasting starting from 5:50.
I understand the basic idea of basis, but I don't think I understood the usage of it in time series data correctly. I have a Pandas dataframe with daily timestamps and target variables. I tried writing radial basis function
def radial_basis(x, month): alpha = 0.5 coef = -1/(2*alpha) return np.exp(coef*(x-month)**2)
and calculating basis for every month (x is row number). This didn't work.
Any tips on how I should try to do this?