Highest‐density forecast regions for nonlinear and non‐normal time series models

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Abstract

Forecast regions are a common way to summarize forecast accuracy. They usually consist of an interval symmetric about the forecast mean. However, symmetric intervals may not be appropriate forecast regions when the forecast density is not symmetric and unimodal. With many modern time series models, such as those which are non‐linear or have non‐normal errors, the forecast densities are often asymmetric or multimodal. The problem of obtaining forecast regions in such cases is considered and it is proposed that highest‐density forecast regions be used. A graphical method for presenting the results is discussed.

Original languageEnglish
Pages (from-to)431-441
Number of pages11
JournalJournal of Forecasting
Volume14
Issue number5
DOIs
Publication statusPublished - 1 Jan 1995

Keywords

  • forecast intervals
  • highest density regions
  • non‐linear time series
  • non‐normal time series
  • threshold models

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