A simple procedure for computing improved prediction intervals for autoregressive models
โ Scribed by Paolo Vidoni
- Book ID
- 111040110
- Publisher
- John Wiley and Sons
- Year
- 2009
- Tongue
- English
- Weight
- 532 KB
- Volume
- 30
- Category
- Article
- ISSN
- 0143-9782
No coin nor oath required. For personal study only.
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Multiple forecasts for autoregressive-integrated moving-average (ARIMA) models are useful in many areas such as economics and business forecasting. In recent years, approximation methods to construct simultaneous prediction intervals for multiple forecasts arc developed. These methods were based on
## Abstract Recent studies on bootstrap prediction intervals for autoregressive (AR) model provide simulation findings when the lag order is known. In practical applications, however, the AR lag order is unknown or can even be infinite. This paper is concerned with prediction intervals for AR model