高斯分布尺度混合后带误差的半参数模型估计

IF 0.6 4区数学 Q4 STATISTICS & PROBABILITY

Brazilian Journal of Probability and Statistics Pub Date : 2021-03-01 DOI:10.1214/20-BJPS476

Marcelo M. Taddeo, P. Morettin

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引用次数: 0

摘要

在本文中，我们考虑了一个半参数回归模型，其中误差遵循高斯分布的比例混合。其目的是使用EM算法和P样条和B样条的近似来估计被假设属于某类函数的目标函数。我们通过几个模拟研究来说明所提出的方法。还研究了其他形式的函数近似，即傅立叶展开和小波展开。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Estimation of semiparametric models with errors following a scale mixture of Gaussian distributions

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.

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来源期刊

Brazilian Journal of Probability and Statistics STATISTICS & PROBABILITY-

CiteScore

1.60

自引率

10.00%

发文量

审稿时长

>12 weeks

期刊介绍： The Brazilian Journal of Probability and Statistics aims to publish high quality research papers in applied probability, applied statistics, computational statistics, mathematical statistics, probability theory and stochastic processes. More specifically, the following types of contributions will be considered: (i) Original articles dealing with methodological developments, comparison of competing techniques or their computational aspects. (ii) Original articles developing theoretical results. (iii) Articles that contain novel applications of existing methodologies to practical problems. For these papers the focus is in the importance and originality of the applied problem, as well as, applications of the best available methodologies to solve it. (iv) Survey articles containing a thorough coverage of topics of broad interest to probability and statistics. The journal will occasionally publish book reviews, invited papers and essays on the teaching of statistics.