I'm dealing with a time series data and I'm trying to construct a time series model for this particular dataset. I'm new to R and tried using the the
auto.arima function under the forecast package:
fit <- auto.arima(tsdata, xreg=cbind(CSS2$Month,CSS2$DayID,CSS2$Year), stepwise=FALSE, approximation=FALSE) summary(fit) resid(fit) acf(resid(fit))
However, I noticed some problems in the ACF plot and the PACF plot from the resulting model. Both of those appear to show some trends or seasonality.
The data that I'm dealing with do have some strong seasonal patterns (on a weekly basis and on a monthly basis), and I thought that this would be captured using
auto.arima. I do have the most recent version of the forecast package.
I should mention that I have daily data for 3 years, so there are a total of 1095 observations.
Any suggestions would be much appreciated, thank you!
ACF Plot PACF Plot