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Extreme value Birnbaum–Saunders regression models applied to environmental data

  • Víctor Leiva
  • Marta Ferreira
  • M. Ivette Gomes
  • Camilo Lillo
Original Paper

Abstract

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.

Keywords

Data analysis Maximum likelihood method Monte Carlo simulation Residuals Statistical modeling 

Notes

Acknowledgments

The authors wish to thank the Editors and three anonymous referees for their constructive comments on an earlier version of this manuscript, which resulted in this improved version. This study was partially supported by the Chilean Council for Scientific and Technological Research under the project grant FONDECYT 1120879, by FEDER Funds through “Programa Operacional de Factores de Competitividade-COMPETE” and by Portuguese Funds through “Fundação para a Ciência e a Tecnologia” (FCT) under the project Grants PEst-OE/MAT/UI0006/2014 (CEAUL) and PEst-OE/MAT/UI0013/2014.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Víctor Leiva
    • 1
    • 2
  • Marta Ferreira
    • 3
  • M. Ivette Gomes
    • 4
  • Camilo Lillo
    • 2
  1. 1.Faculty of Engineering and SciencesUniversidad Adolfo Ibáñez, Viña del MarSantiagoChile
  2. 2.Institute of StatisticsUniversidad de ValparaísoValparaisoChile
  3. 3.Centre of MathematicsUniversidade do MinhoBragaPortugal
  4. 4.Centre of Statistics and Applications (CEAUL)Universidade de LisboaLisbonPortugal

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