Gokalp Yavuz Fulya, Arslan Olcay
Department of Statistics, Middle East Technical University, Ankara, Turkey.
Department of Statistics, Ankara University, Ankara, Turkey.
J Appl Stat. 2019 Dec 18;47(11):2025-2043. doi: 10.1080/02664763.2019.1702928. eCollection 2020.
Variable selection in elliptical Linear Mixed Models (LMMs) with a shrinkage penalty function (SPF) is the main scope of this study. SPFs are applied for parameter estimation and variable selection simultaneously. The smoothly clipped absolute deviation penalty (SCAD) is one of the SPFs and it is adapted into the elliptical LMM in this study. The proposed idea is highly applicable to a variety of models which are set up with different distributions such as normal, student-, Pearson VII, power exponential and so on. Simulation studies and real data example with one of the elliptical distributions show that if the variable selection is also a concern, it is worthwhile to carry on the variable selection and the parameter estimation simultaneously in the elliptical LMM.
具有收缩惩罚函数(SPF)的椭圆线性混合模型(LMMs)中的变量选择是本研究的主要内容。SPF 同时应用于参数估计和变量选择。平滑截断绝对偏差惩罚(SCAD)是其中一种 SPF,本研究将其应用于椭圆 LMM。所提出的想法高度适用于各种具有不同分布(如正态分布、学生分布、皮尔逊 VII 分布、幂指数分布等)的模型。对其中一种椭圆分布进行的模拟研究和实际数据示例表明,如果变量选择也是一个关注点,那么在椭圆 LMM 中同时进行变量选择和参数估计是值得的。