Abstract
In this project we present an inferential study of censored measurement error-in-variables models under the class of scale mixtures of normal distributions, from a classical and Bayesian perspective. We present an interesting EM algorithm for maximum likelihood Estimation, as well as, the Gibbs Sampling to proceed with Bayesian inference. The proposed algorithms are implemented in the R …