Evaluation and prediction under hierarchical and bivariate copula models for seat belt use data

DOI10.1007/s42519-021-00191-2zbMath1480.62244OpenAlexW3156570412MaRDI QIDQ2241473

J. Kannane, B. E. Porter, Norou Diawara

Publication date: 9 November 2021

Published in: Journal of Statistical Theory and Practice (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s42519-021-00191-2

zbMATH Keywords

predictionshierarchical modelsbivariate copulaseat belt use

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Applications of statistics to social sciences (62P25) Characterization and structure theory for multivariate probability distributions; copulas (62H05) Reliability and life testing (62N05)

Uses Software

• lme4

Cites Work

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• Generalized extreme value regression for binary response data: an application to B2B electronic payments system adoption
• An introduction to copulas.
• Extreme value analysis of environmental time series: an application to trend detection in ground-level ozone. With comments and a rejoinder by the author
• Laws of Small Numbers: Extremes and Rare Events
• Modelling small and medium enterprise loan defaults as rare events: the generalized extreme value regression model

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