ABSTRACT
Modeling for time series is conceptually similar to other modeling problems, but one major distinction is that usually the next value of the series is highly related to the most recent values, with a time-decaying importance in this relationship to previous values. Because of this property a different set of machinery has evolved for the special case of time series modeling, sometimes loosely called forecasting or even prediction.
