Multivariate semi-Weibull distributions

DOI10.1016/j.jmva.2009.01.015zbMath1163.62040OpenAlexW1984707490MaRDI QIDQ1026347

Hsiaw-Chan Yeh

Publication date: 24 June 2009

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2009.01.015

zbMATH Keywords

characterizationsdomain of partial attractionMSWgeometric minima-infinite divisibilityhomogeneous MSW distributionminima-infinite divisibilityminima-semi-stabilityMO-MSP distributionsMO-MSWMSP

Mathematics Subject Classification ID

Infinitely divisible distributions; stable distributions (60E07) Characterization and structure theory for multivariate probability distributions; copulas (62H05) Characteristic functions; other transforms (60E10)

Related Items

Characterizations of the General Multivariate Weibull Distributions ⋮ General Multivariate Weibull Processes ⋮ Multivariate semi-logistic distributions ⋮ Multivariate Weibull and Pareto Distributions in Hilbert Space

Cites Work

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• Bivariate semi-Pareto minification processes.
• Three general multivariate semi-Pareto distributions and their characterizations
• Multivariate distributions having Weibull properties
• Asymptotic independence and perfect dependence of vector components of multivariate extreme statistics
• Bivariate semi-Pareto distributions and processes
• Some properties and characterizations for generalized multivariate Pareto distributions
• Domains of attraction of multivariate extreme value distributions
• Domains of geometric partial attraction of max-semistable laws: Structure, merge and almost sure limit theorems
• Sur la distribution limite du terme maximum d'une série aléatoire
• Semi-Pareto processes
• Fitting a multivariate failure time distribution
• Some Related Minima Stability and Minima Infinite Divisibility of the General Multivariate Pareto Distributions
• On solutions to min $$(X,{\text{ Y}})\mathop = \limits^d aX$$ and min $$(X,{\text{ Y}})\mathop = \limits^d aX\mathop = \limits^d bY$$
• A new method for adding a parameter to a family of distributions with application to the exponential and Weibull families
• A Class of Multivariate Survival Functions Characterized by Minimum and Marginal Distribution
• A Multivariate Exponential Distribution