Robust statistical modeling using the Birnbaum-Saunders-t distribution applied to insurance

Gilberto A. Paula; Víctor Leiva; Michelli Barros; Shuangzhe Liu

doi:10.1002/asmb.887

Robust statistical modeling using the Birnbaum-Saunders-t distribution applied to insurance

Gilberto A. Paula, Víctor Leiva, Michelli Barros, Shuangzhe Liu

Resultado de la investigación: Contribución a una revista › Artículo › revisión exhaustiva

83 Citas (Scopus)

Resumen

In this paper, we carry out robust modeling and influence diagnostics in Birnbaum-Saunders (BS) regression models. Specifically, we present some aspects related to BS and log-BS distributions and their generalizations from the Student-t distribution, and develop BS-t regression models, including maximum likelihood estimation based on the EM algorithm and diagnostic tools. In addition, we apply the obtained results to real data from insurance, which shows the uses of the proposed model.

Idioma original	Inglés
Páginas (desde-hasta)	16-34
Número de páginas	19
Publicación	Applied Stochastic Models in Business and Industry
Volumen	28
N.º	1
DOI	https://doi.org/10.1002/asmb.887
Estado	Publicada - ene. 2012
Publicado de forma externa	Sí

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abstract = "In this paper, we carry out robust modeling and influence diagnostics in Birnbaum-Saunders (BS) regression models. Specifically, we present some aspects related to BS and log-BS distributions and their generalizations from the Student-t distribution, and develop BS-t regression models, including maximum likelihood estimation based on the EM algorithm and diagnostic tools. In addition, we apply the obtained results to real data from insurance, which shows the uses of the proposed model.",

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KW - generalized Birnbaum-Saunders and sinh-normal distributions

KW - influence diagnostics

KW - likelihood methods

KW - log-linear models

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Robust statistical modeling using the Birnbaum-Saunders-t distribution applied to insurance

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