Resumen de Bayesian Prediction in Threshold Autoregressive Models with Exponential White Noise

Isabel Pereira Rodríguez, M. A. Amaral Turkman

• In this paper, we develop a Bayesian analysis of a threshold autoregressive model with exponential noise. An approximate Bayes methodology, which is introduced here, and the Gibbs sampler are used to compute marginal posterior densities for the parameters of the model, including the threshold parameter, and to compute one-step-ahead predictive density functions. The proposed methodology is illustrated with a simulation study and a real example.