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Answer: More applicable but decreases the number of observations in the modeling procedure.
## Explanation In the Peaks Over Threshold (POT) approach of Extreme Value Theory: - **Setting a higher threshold** makes the model **more applicable** because it focuses on more extreme events that better fit the generalized Pareto distribution (GPD) used in POT modeling. Higher thresholds ensure we're modeling true extremes rather than moderate events. - However, **setting a higher threshold decreases the number of observations** available for modeling because fewer data points exceed the threshold. This creates a trade-off between having enough data for reliable parameter estimation and focusing on sufficiently extreme events. Therefore, option C is correct: **"More applicable but decreases the number of observations in the modeling procedure."** This trade-off is fundamental in POT modeling - practitioners must balance threshold selection to ensure both model applicability (sufficiently extreme events) and adequate sample size for parameter estimation.
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In setting the threshold in the POT approach, which of the following statements is the most accurate? Setting the threshold relatively high makes the model:
A
Less applicable but increases the number of observations in the modeling procedure.
B
Less applicable and decreases the number of observations in the modeling procedure.
C
More applicable but decreases the number of observations in the modeling procedure.
D
More applicable but increases the number of observations in the modeling procedure.