# ARMA model for Time Series about volumes? GARCH?

I am trying to do some analysis and forecasting about a Time Series which is about volumes (how many people call to a call center per hour). I have about 2000 observations, in hourly data. I am aware that there are some gaps between hours (i.e. 3am no one calls).

I'd like to model the level of volume but I am doubting with which model to use. From a preliminar analysis I've done, the ACF of the level has clearly some seasonality. I attach a picture of the level and another of the ACF.

I have been thinking quite hard which model can be appropriate but I'm doubting. I'd thought in a Multiplicative Error Model (MEM), some ARMA-type model or a GARCH-type model. However I am very doubtful which is an interesting approach.

I'd really appreciate any suggestion!

I'd rather recommend that you look into forecasting methods that were specifically designed to deal with multiple seasonalities. One good algorithm is implemented in tbats() in the forecast package for R.