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May 2021 Estimation of semiparametric models with errors following a scale mixture of Gaussian distributions
Marcelo M. Taddeo, Pedro A. Morettin
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Braz. J. Probab. Stat. 35(2): 315-334 (May 2021). DOI: 10.1214/20-BJPS476

Abstract

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.

Acknowledgments

The authors are grateful for the partial support from grants of CNPq (MMT) and FAPESP 2018/04654-9(PAM).

Citation

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Marcelo M. Taddeo. Pedro A. Morettin. "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

Information

Received: 1 December 2019; Accepted: 1 May 2020; Published: May 2021
First available in Project Euclid: 24 March 2021

Digital Object Identifier: 10.1214/20-BJPS476

Rights: Copyright © 2021 Brazilian Statistical Association

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Vol.35 • No. 2 • May 2021
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