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A SUCCESSIVE FILTERING TECHNIQUE FOR IDENTIFYING LONG-TERM TRENDS

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dc.contributor.author ASSIMAKOPOULOS, V en
dc.date.accessioned 2014-03-01T01:10:46Z
dc.date.available 2014-03-01T01:10:46Z
dc.date.issued 1995 en
dc.identifier.issn 0277-6693 en
dc.identifier.uri https://dspace.lib.ntua.gr/xmlui/handle/123456789/11433
dc.subject CYCLES en
dc.subject FILTERS en
dc.subject LONG-TERM TRENDS en
dc.subject.classification Management en
dc.subject.classification Planning & Development en
dc.title A SUCCESSIVE FILTERING TECHNIQUE FOR IDENTIFYING LONG-TERM TRENDS en
heal.type journalArticle en
heal.identifier.primary 10.1002/for.3980140104 en
heal.identifier.secondary http://dx.doi.org/10.1002/for.3980140104 en
heal.language English en
heal.publicationDate 1995 en
heal.abstract The most reliable component of a time series, for forecasting purposes, is the shape of the long-term trend. However, the presence of cycles makes it difficult to identify and predict the changes in such trends. While up to now emphasis has been given in identifying and measuring cyclical behaviour, this paper presents a technique that aims at removing cyclical effects from the long-term trends. This technique is based on a transformation that is successively applied on the original time series. Each time the transformation is applied, an observation is selected and replaced by the average of its adjacent observations. This results in the elimination of the cyclical component. Independently of their depth, the cycles are being removed in ascending order relatively to their length. This leads to 'brushing off' the long-term trends from any cyclical effects. A specialized software has been developed in Pascal. The proposed technique was applied in a set of time series from the M2- and M-competition and the results are presented in this paper. en
heal.publisher JOHN WILEY & SONS LTD en
heal.journalName JOURNAL OF FORECASTING en
dc.identifier.doi 10.1002/for.3980140104 en
dc.identifier.isi ISI:A1995QF66700003 en
dc.identifier.volume 14 en
dc.identifier.issue 1 en
dc.identifier.spage 35 en
dc.identifier.epage 43 en


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