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Time‐simultaneous prediction band for a time series
Author(s) -
Kolsrud Dag
Publication year - 2007
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.1020
Subject(s) - series (stratigraphy) , computer science , univariate , time series , sample (material) , parametric statistics , econometrics , statistics , mathematics , machine learning , multivariate statistics , paleontology , chemistry , chromatography , biology
I propose principles and methods for the construction of a time‐simultaneous prediction band for a univariate time series. The methods are entirely based on a learning sample of time trajectories, and make no parametric assumption about its distribution. Hence, the methods are general and widely applicable. The expected coverage probability of a band can be estimated by a bootstrap procedure. The estimate is likely to be less than the nominal level. Expected lack of coverage can be compensated for by increasing the coverage in the learning sample. Applications to simulated and empirical data illustrate the methods. Copyright © 2007 John Wiley & Sons, Ltd.