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Automated selection of $r$ in $r$-largest order statistics models: finite-sample performance and return-level inference
Selecting the number $r$ of upper order statistics is a key practical issue in fitting $r$-largest order statistics models. The entropy difference test for selecting $r$ relies on a large-sample approximation. The score test can be used for small samples but is computationally demanding. To obtain a
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