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Highest‐density forecast regions for nonlinear and non‐normal time series models
Author(s) -
Hyndman Rob J.
Publication year - 1995
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/for.3980140503
Subject(s) - series (stratigraphy) , forecast error , interval (graph theory) , forecast verification , nonlinear system , econometrics , mathematics , time series , statistics , computer science , geology , paleontology , physics , combinatorics , quantum mechanics
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.