What type of study is this?

This is a Quantitative Study study.

October 20, 2025Open Access

Moderately Heavy Extreme Values under Extreme Long Range Dependence

View Full Paper

Ask AI

Bookmark

The study investigates stationary sequences with subexponential tails, focusing on their extreme value behaviors.
Findings indicate that extreme values arise from multiple significant values clustered together due to long range dependence.
Functional extremal limit theorems are established to characterize these phenomena with non-Gumbel objects.
The results enrich our understanding of dependencies in extreme values through fractal analysis and limit theorems.

Implication

This analysis reveals the clustering of extreme values in stationary sequences, highlighting their fractal features and dependence patterns.

Abstract

We consider stationary sequences whose marginal tail is subexponential and lies in the Gumbel Maximum domain of attraction. Due to the extremely strong dependence, their extreme values are caused by multiple big values and are clustered in the large scale with fractal features. We establish functional extremal limit theorems with non-Gumbel limit objects to characterize these delicate phenomena.

Discussion

No takes yet. Share an insight, caveat, or question.

Cite This Study

Zaoli Chen (2025) studied this question.

synapsesocial.com/papers/68f5fcdc8d54a28a75cf22de https://doi.org/10.48550/arxiv.2505.23103

View Full Paper

Ask AI

Bookmark

Implication

This analysis reveals the clustering of extreme values in stationary sequences, highlighting their fractal features and dependence patterns.

Moderately Heavy Extreme Values under Extreme Long Range Dependence

Key Points

Implication

Abstract

Discussion

Cite This Study

Moderately Heavy Extreme Values under Extreme Long Range Dependence

Key Points

Implication

Abstract

Discussion

Cite This Study

Keep reading

Keep reading