My aim is to forecast the daily number of registrations in two different channels.
Weekly seasonality is quite strong. Especially the difference between the weekends and the rest of the week is big. I also observe annual effects. Moreover, I have a few special event days, which significantly differ from the others days. Here is the dataset.
First, I applied a TBATS model on these two channels.
x.msts <- msts(Channel1_reg,seasonal.periods=c(7,365.25))
# fit model
fit <- tbats(x.msts)
fit
plot(fit)
forecast_channel1 <- forecast(fit,h=30)
First channel:
TBATS(0, {2,3}, -, {<7,3>, <365.25,2>})
Call: tbats(y = x.msts)
Parameters
Lambda: 0
Alpha: 0.0001804516
Gamma-1 Values: -1.517954e-05 1.004701e-05
Gamma-2 Values: -3.059654e-06 -2.796211e-05
AR coefficients: 0.249944 0.544593
MA coefficients: 0.215696 -0.361379 -0.21082
Second channel:
BATS(0, {2,2}, 0.929, -)
Call: tbats(y = y.msts)
Parameters
Lambda: 0
Alpha: 0.1652762
Beta: -0.008057904
Damping Parameter: 0.928972
AR coefficients: -0.586163 -0.676921
MA coefficients: 0.924758 0.743675
If I forecast the second channel, I only get blank values instead of any forecasts.
Could you please help why is that so? Do you have any suggestion how to build in the specific event days into this model?