Palestras e Seminários

26/05/2017

17:00

Auditório Prof. Luiz Antonio Fávaro

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Apresentador: Jorge Bazán, ICMC/USP

Coautores: Francisco Torres-Avilés, Adriano K. Suzuki, Francisco Louzada.

Resumo: In binary regression, symmetric links such as logit and probit are
usually considered as standard. However, in the presence of unbalancing of
ones and zeros, these links can be inappropriate and inflexible to fit the
skewness in the response curve and likely to lead to misspecification. This
is the case of covering some type of insurance, where it can be observed that
the probability of a given binary response variable approaches zero at
different rates than it approaches one. Furthermore, when usual links are
considered, there is not a skewness parameter associated with the
distribution chosen that, regardless of the linear predictor, is easily
interpreted. In order to overcome such problems, a proposal for the
construction of a set of new skew links is developed in this paper, where
some of their properties are discussed. In this context, power links and
their reversal versions are presented. A Bayesian inference approach using
MCMC is developed for the presented models. The methodology is illustrated
considering a sample of motor insurance policyholders selected randomly by
gender. Results suggest that the proposed link functions are more appropriate
than other alternative link functions commonly used in the literature.

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