Robust Diagnostics for Linear Mixed Models with the Forward Search

被引：0
|
作者：
Corbellini, Aldo [1 ,2 ]
Grossi, Luigi [3 ,4 ]
Laurini, Fabrizio [1 ,2 ]
机构：
[1] Univ Parma, Ro SA, Parma, Italy
[2] Univ Parma, Dept Econ, Parma, Italy
[3] Univ Padua, Ro SA, Padua, Italy
[4] Univ Padua, Dept Stat Sci, Padua, Italy
来源：
BUILDING BRIDGES BETWEEN SOFT AND STATISTICAL METHODOLOGIES FOR DATA SCIENCE | 2023年 / 1433卷
关键词：
D O I：
10.1007/978-3-031-15509-3_11
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Robustness of Linear Mixed Models (LMM) with random effects is investigated with the forward search (FS). Extending the FS to LMM offers new computational challenges, as some restrictions, imposed by the model and their estimates, are required. The method is illustrated by an application to real data where exports of coffee to European Union are analyzed to identify outliers that might be linked to potential frauds. An additional short simulation is presented to strengthen the usefulness of the proposed method.
引用
收藏
页码：79 / 86
页数：8
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