an introduction to hybrid method for interval-valued time series

Interval-valued data appear quite naturally in many situations in whichthe values of each observation are defined by two points, a lower and an upper limits.this paper presents hybrid method to forecast the interval-valued time series. hybridmodel is a nonlinear method that is the additive combination of autoregressiveintegrated moving average and artificial neural networks models. the performance ofthe estimation procedure and prediction methods is evaluated via a simulation study.then, our methodology is illustrated on a practical data set.