Forecasting Data Published at Irregular Time Intervals Using an Extension of Holt's Method
In practice many data series contain observations at irregular times whereas most forecasting methods are restricted to the case of equal time intervals between data points. This paper provides extensions of Single Exponential Smoothing and Holt's Method to the case of irregularly spaced data and shows them to be highly efficient computationally. The new methods are applied to six published series, and their performance is analyzed via four error measures with respect to changes in the smoothing parameters.
Year of publication: |
1986
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Authors: | Wright, David J. |
Published in: |
Management Science. - Institute for Operations Research and the Management Sciences - INFORMS, ISSN 0025-1909. - Vol. 32.1986, 4, p. 499-510
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Publisher: |
Institute for Operations Research and the Management Sciences - INFORMS |
Keywords: | forecasting/irregularly spaced data |
Saved in:
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