Forecast intervals typically depend upon an assumption of normal forecast errors due to lack of information concerning the distribution of the forecast. This article applies the bootstrap to the problem of estimating forecast intervals for an AR(p) model. Box-Jenkins intervals are compared to interv
✦ LIBER ✦
Iterated bootstrap with applications to frontier models
✍ Scribed by Peter Hall; Wolfgang Härdle; Léopold Simar
- Publisher
- Springer
- Year
- 1995
- Tongue
- English
- Weight
- 697 KB
- Volume
- 6
- Category
- Article
- ISSN
- 0895-562X
No coin nor oath required. For personal study only.
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## Abstract This paper proposes the use of the bias‐corrected bootstrap for interval forecasting of an autoregressive time series with an arbitrary number of deterministic components. We use the bias‐corrected bootstrap based on two alternative bias‐correction methods: the bootstrap and an analytic