Generalized Extreme Value Regression: an Application to Credit Defaults

نویسندگان

  • Raffaella Calabrese
  • Silvia Osmetti
  • Angela
چکیده

We aim at proposing a Generalized Linear Model (GLM) with binary dependent variable Y , whose link function defined by the Generalized Extreme Value (GEV) distribution. We define this model as GEV regression. The goal of this paper is to overcome the drawbacks shown by the logistic regression in rare events: the probability of rare events is underestimated and the logit link is a symmetric function. Let Y denote a binary response variable and let X be an explanatory variable, the logistic response curve is

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تاریخ انتشار 2011