On the asymptotic independence of the sum and rare values of weakly dependent stationary random variables

DOI10.1016/0304-4149(95)00054-2zbMath0848.60026OpenAlexW1967258484MaRDI QIDQ1909952

Tailen Hsing

Publication date: 8 October 1996

Published in: Stochastic Processes and their Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0304-4149(95)00054-2

zbMATH Keywords

point processstrong mixingcentral limit theoremsextreme value

Mathematics Subject Classification ID

Gaussian processes (60G15) Central limit and other weak theorems (60F05) Stationary stochastic processes (60G10)

Related Items (5)

The Joint Distribution of the Sum and the Maximum of IID Exponential Random Variables ⋮ The joint distribution of the sum and maximum of dependent Pareto risks ⋮ A new multivariate model involving geometric sums and maxima of exponentials ⋮ Ordered random variables ⋮ A bootstrap approximation to the joint distribution of sum and maximum of a stationary sequence

Cites Work

• Unnamed Item
• Unnamed Item
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• Unnamed Item
• Extremes and related properties of random sequences and processes
• Convergence to a stable distribution via order statistics
• On some estimates based on sample behavior near high level excursions
• Point process and partial sum convergence for weakly dependent random variables with infinite variance
• A note on the asymptotic independence of the sum and maximum of strongly mixing stationary random variables
• The joint limiting distribution of sums and maxima of stationary sequences
• Sums and maxima in stationary sequences
• Sums and maxima of discrete stationary processes
• On the asymptotic joint distribution of the sum and maximum of stationary normal random variables

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