Extreme value Birnbaum–Saunders regression models applied to environmental data

Extreme value models are widely used in different areas. The Birnbaum–Saunders distribution is receiving considerable attention due to its physical arguments and its good properties. We propose a methodology based on extreme value Birnbaum–Saunders regression models, which includes model formulation...

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Bibliographic Details
Published in:Stochastic environmental research and risk assessment 2016-03, Vol.30 (3), p.1045-1058
Main Authors: Leiva, Víctor, Ferreira, Marta, Gomes, M. Ivette, Lillo, Camilo
Format: Article
Language:English
Subjects:
Aquatic Pollution
Chemistry and Earth Sciences
Computational Intelligence
Computer Science
Computer simulation
Earth and Environmental Science
Earth Sciences
Ecological risk assessment
Environment
Environmental extremism
Extreme values
Math. Appl. in Environmental Science
Methodology
Monte Carlo simulation
Original Paper
Physics
Probability Theory and Stochastic Processes
Receiving
Regression
Regression analysis
Risk assessment
Statistical analysis
Statistics for Engineering
Waste Water Technology
Water Management
Water Pollution Control
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Summary:Extreme value models are widely used in different areas. The Birnbaum–Saunders distribution is receiving considerable attention due to its physical arguments and its good properties. We propose a methodology based on extreme value Birnbaum–Saunders regression models, which includes model formulation, estimation, inference and checking. We further conduct a simulation study for evaluating its performance. A statistical analysis with real-world extreme value environmental data using the methodology is provided as illustration.
ISSN:1436-3240
1436-3259
DOI:10.1007/s00477-015-1069-6