1 Trend and Cycle Decomposition y t = t + t where y t is an n 1 vector and t and t represent trend and cycle components respectively. This decomposition into components is not unique. Beveridge and Nelson (1981) and Stock and Watson (1988) derive the following decomposition: y t = C(L)" t = C(1)" t + (1 L)C (L)" t Integrating up gives: y t = C(1) 1 X i=0 " ti | {z } + C (L)" t | {z } trend cycl...

We review regression models for count time series. We discuss the approach which is based on generalized linear models and the class of integer autoregressive processes. The generalized linear models framework provides convenient tools for implementing model fitting and prediction using standard software. Furthermore, this approach provides a natural extension to the traditional ARMA methodolog...

The point-valued time series (PTS) is simply about one value in each or period of the data, but when data have two values at time, suitable called interval-valued (ITS). An example ITS daily close and open stock prices. If are typed linguistic for example, “low increase”, “medium increase” “high a fuzzy-valued being well-known as fuzzy (FTS). aim this study to compare PTS FTS models forecasting...