In this paper, we consider a semiparametric regression model where the error follows a scale mixture of Gaussian distributions. The purpose is to estimate the target function which is assumed to belong to some class of functions using the EM algorithm and approximations via P-splines and B-splines. We illustrate the proposed methodology through several simulation studies. Other forms of function approximation are also studied, namely Fourier and wavelet expansions.
The authors are grateful for the partial support from grants of CNPq (MMT) and FAPESP 2018/04654-9(PAM).
"Estimation of semiparametric models with errors following a scale mixture of Gaussian distributions." Braz. J. Probab. Stat. 35 (2) 315 - 334, May 2021. https://doi.org/10.1214/20-BJPS476