A numerical nonmetric approach for analyzing time series data |
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Authors: | Adi Raveh |
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Affiliation: | Hebrew University , Jerusalem and Stanford University, California |
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Abstract: | A numerical nonmetric approach to data analysis of periodic series with polytone trend is suggested. Estimation is made of thesmallest number of tone (monotone segments) possible for the trend. The seasonal component is estimated without need for first removing the (estimated) polytone trend. A computer program has been developed which enables analysis of arbitrary series, either by a prespecified length of period or by estimating the period length if not known in advance. Robustness of the proposed approach enables analysis of very short series, series with missing values, and other series with limitations that cannot be easily handled otherwise. In a separate appendix some empirical results obtained by this approach are compared with those from the X-ll program; this appendix will be sent upon request. |
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Keywords: | Guttman's coefficients of monotonieity linear-periodic transformation nonmetric piecewise monotone polytone seasonal pattern |
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