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AN EMPIRICAL EVALUATION OF INDIVIDUAL ITEM FORECASTING MODELS
Author(s) -
McLeavey Dennis W.,
Lee T. S.,
Adam Everett E.
Publication year - 1981
Publication title -
decision sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.238
H-Index - 108
eISSN - 1540-5915
pISSN - 0011-7315
DOI - 10.1111/j.1540-5915.1981.tb00122.x
Subject(s) - exponential smoothing , computer science , econometrics , demand forecasting , smoothing , noise (video) , operations research , artificial intelligence , economics , mathematics , computer vision , image (mathematics)
A computer simulation experiment was replicated to correct errors in an earlier paper and to compare seven individual item forecasting models across five different demand patterns. Results confirm previous findings that the better forecasting model depends upon the demand pattern and the forecast horizon, as well as the noise level. Nevertheless, exponential double smoothing emerged as the most robust model.