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- W1567340898 abstract "We develop a Bayesian hierarchical logistic regression model to predict the credit risk of companiers classified in different sectors. Explanatory variables derived by experts from balance-sheets are included. Markov chain Monte Carlo (MCMC) methods are used to estimate the proposed model. In particular we show how the delaying rejection strategy outperforms the standart Metrtopolis-Hastings algorithm in terms of asymptotic efficiency of the resulting estimates. The advantages of our over others proposed in the literature are discussed and tested via cross-validation procedures." @default.
- W1567340898 created "2016-06-24" @default.
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- W1567340898 date "2003-10-01" @default.
- W1567340898 modified "2023-09-27" @default.
- W1567340898 title "Bayesian estimate of credit risk via MCMC with delayed rejection" @default.
- W1567340898 hasPublicationYear "2003" @default.
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