Hello, I am trying to create an arima forecast model using fpp3 package in R. I am trying to use an ARIMA model, it looks like my data has some season component, but hard to tell. Here are the ACF + PACF visuals of the 3 groups - (A, B,C). I am trying to forecast number of clients in each group for the next 1 year and so, I am using the fpp3 package.
So far I have tried the generic ARIMA model and another two I thought would be accurate (arima007 + arima_s) but it wasn't. This is my code:
model <- data_stretch %>% model( arima = ARIMA(volume), arima007 = ARIMA(volume ~ pdq(0,0,7)), arima_s = ARIMA(volume ~ pdq(0,0,7)) + PDQ(0,0,0)) )
Here is what the data looks like for category A when plotted:
if someone could please help me write my code and help me figure out the best pdq and PDQ values based on my ACF and PACF visuals, that would be much appreciated. Thank you