Bayesian Estimation for the Extended t-process Regression Models with Independent Errors

The extended t-process regression model is developed to robustly model functional data with outlier functional curves.This paper applies Bayesian estimation to propose an estimation procedure for the model with independent errors.A Monte Carlo EM method is built to estimate parameters involved in the model.Simulation studies and real examples show the proposed method performs well against outliers.