Abstract
Multistep prediction error methods for linear time series models are considered from both a theoretical and a practical standpoint. The emphasis is on autoregressive moving‐average (ARMA) models for which a multistep prediction error estimation method (PEM) is developed. The results of a Monte Carlo simulation study aimed at establishing the possible merits of the multistep PEM are presented.
| Original language | English |
|---|---|
| Pages (from-to) | 357-368 |
| Number of pages | 12 |
| Journal | Journal of Forecasting |
| Volume | 8 |
| Issue number | 4 |
| DOIs | |
| State | Published - 1989 |
Keywords
- ARMA models
- Gradient algorithms
- One‐step and multistep methods
- Prediction error methods
- Prediction performance assessment