Abstract
Changes in time series often occur gradually so that there is a certain amount of fuzziness in the change point. In this paper we have presented an integrated identification procedure for change-point detection based on fuzzy logic. The membership function of each datum corresponding to the cluster centres is calculated and is used for performance index grouping. We have also suggested a test for the change in level and the change in slope for testing a hypothesis about change points. We have made simulation studies to demonstrate the whole procedure. Finally an empirical study about change-point identification in the exchange rate data of six Asian nations has been demonstrated using the algorithm of the paper.
| Original language | English |
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| Pages (from-to) | 1185-1192 |
| Number of pages | 8 |
| Journal | International Journal of Systems Science |
| Volume | 32 |
| Issue number | 9 |
| DOIs | |
| Publication status | Published - 1 Sept 2001 |