Analysis of estimation methods for the extremal index
Many datasets present time-dependent variation and short-term clustering within extreme values. The extremal index is a primary measure to evaluate clustering of high values in a stationary sequence. Estimation procedures are based on the choice of a threshold and/or a declustering parameter or a bl...
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| Format: | article |
| Language: | eng |
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2018
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| Online Access: | http://hdl.handle.net/1822/55225 |
| Country: | Portugal |
| Oai: | oai:repositorium.sdum.uminho.pt:1822/55225 |
| Summary: | Many datasets present time-dependent variation and short-term clustering within extreme values. The extremal index is a primary measure to evaluate clustering of high values in a stationary sequence. Estimation procedures are based on the choice of a threshold and/or a declustering parameter or a block size. Here we revise several different methods and compare them through simulation. In particular, we will see that a recent declustering methodology may be useful for the popular runs estimator and for a new estimator that works under the validation of a local dependence condition. An application to real data is also presented. |
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