期刊文献+
共找到1篇文章
< 1 >
每页显示 20 50 100
Variable Selection for Robust Mixture Regression Model with Skew Scale Mixtures of Normal Distributions
1
作者 Tingzhu Chen Wanzhou Ye 《Advances in Pure Mathematics》 2022年第3期109-124,共16页
In this paper, we propose a robust mixture regression model based on the skew scale mixtures of normal distributions (RMR-SSMN) which can accommodate asymmetric, heavy-tailed and contaminated data better. For the vari... In this paper, we propose a robust mixture regression model based on the skew scale mixtures of normal distributions (RMR-SSMN) which can accommodate asymmetric, heavy-tailed and contaminated data better. For the variable selection problem, the penalized likelihood approach with a new combined penalty function which balances the SCAD and l<sub>2</sub> penalty is proposed. The adjusted EM algorithm is presented to get parameter estimates of RMR-SSMN models at a faster convergence rate. As simulations show, our mixture models are more robust than general FMR models and the new combined penalty function outperforms SCAD for variable selection. Finally, the proposed methodology and algorithm are applied to a real data set and achieve reasonable results. 展开更多
关键词 robust mixture regression Model Skew Scale mixtures of Normal Distributions EM Algorithm SCAD Penalty
下载PDF
上一页 1 下一页 到第
使用帮助 返回顶部