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Effective lengths of intervals to improve forecasting in fuzzy time series. (English) Zbl 0992.91077

Summary: Length of intervals affects forecasting results in fuzzy time series. Unfortunately, the issue of how to determine effective lengths of intervals has not been touched in previous studies. This study proposes distribution- and average-based length to approach this issue. Distribution-based length is the largest length smaller than at least half the first differences of data. Average-based length is set to one half the average of the first differences of data. Empirical analyses show that distribution- and average-based lengths are simple to calculate and can greatly improve forecasting results; in particular, they are superior to the randomly chosen lengths used in previous studies.

MSC:

91B84 Economic time series analysis
62A86 Fuzzy analysis in statistics
62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH)
03E72 Theory of fuzzy sets, etc.
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References:

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