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The accuracy of extrapolation methods; an automatic box–jenkins package sift
Author(s) -
Hill Gareth,
Fildes Robert
Publication year - 1984
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.3980030309
Subject(s) - box–jenkins , extrapolation , computer science , identification (biology) , series (stratigraphy) , scale invariant feature transform , artificial intelligence , data mining , algorithm , pattern recognition (psychology) , machine learning , time series , statistics , mathematics , autoregressive integrated moving average , feature extraction , paleontology , botany , biology
Hill and Woodworth (1980) proposed an algorithm suitable for identifying Box–Jenkins models automatically without reliance on the investigator. This paper first reviews the method. It is then used on the 111 series analysed by Anderson in the Makridakis forecasting competition. The results show that the automatic method of Hill and Woodworth is comparable in terms of accuracy to the full Box–Jenkins identification procedure.