Non-Gaussian regression models with correlated errors

Music City Center 

We introduce non-Gaussian regression models with serially correlated errors and propose an estimation method for the models. We incorporate an additional parameter into the regression models in order to induce normality and then, simultaneously estimate all the parameters. To this end we explore a posterior estimation method on the wavelet domain. Performances are assessed using simulation studies.

Non-Gaussian

Posterior estimation

Regression

Serially Correlated

Wavelet Transform 

Section on Statistical Computing