Censored Regression with Serially Correlated Errors: a Bayesian approach
序列相关误差下删失回归的贝叶斯方法
The problem of estimating censored linear regression models with autocorrelated errors arises in many environmental and social studies. The present work proposes a Bayesian approach to estimate censored regression models with AR(p) errors. The algorithm developed here considers the Gibbs sampler with data augmentation(GDA), in which, at each iteration, both the model parameters and the latent variables are sampled. The data augmentation is achieved from multiple sampling of…