Modelling skewed and heavy-tailed data using a normal weighted inverse Gaussian distribution

DOI10.16929/as/2022.3165.300zbMath1498.62040OpenAlexW4293213689MaRDI QIDQ2097004

Patrick Guge Weke, Carolyne Adhiambo Ogutu, Calvin Maina, Joseph Makoteku Ottieno

Publication date: 11 November 2022

Published in: Afrika Statistika (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/journals/afrika-statistika/volume-17/issue-1/Modelling-Skewed-And-Heavy-tailed-Data-Using-A-Normal-Weighted/10.16929/as/2022.3165.300.full

zbMATH Keywords

EM-algorithmmixing distributionfinite mixture

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05) Probability distributions: general theory (60E05) Characterization and structure theory of statistical distributions (62E10)

Cites Work

• An EM type algorithm for maximum likelihood estimation of the normal-inverse Gaussian distribution
• Mean mixtures of normal distributions: properties, inference and application
• Estimation methods for expected shortfall
• Generalized Poisson–Lindley Distribution
• Normal Inverse Gaussian Distributions and Stochastic Volatility Modelling
• Weighted inverse Gaussian – a versatile lifetime model
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