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An examination of the accuracy of judgemental confidence intervals in time series forecasting
Author(s) -
O'Connor Marcus,
Lawrence Michael
Publication year - 1989
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.3980080207
Subject(s) - exponential smoothing , confidence interval , series (stratigraphy) , calibration , statistics , econometrics , smoothing , mathematics , exponential distribution , paleontology , biology
This paper examines the accuracy (calibration) of judgemental and selected statistical confidence intervals in time series forecasting. Using the forecasts and forecast errors produced by the deseasonalized single exponential smoothing method, three statistical intervals were produced utilizing three assumptions about the distribution of errors: the normal distribution, the empirical distribution and the distribution based on the Chebyshev inequality. Using 33 real‐life time series, results indicated that the judgemental confidence intervals were initially excessively overconfident, thus confirming the finding of Lichtenstein et al. (1982). However, calibration of the judgemental intervals improved considerably with feedback, and was found to be influenced by the degree of forecasting difficulty of the series.