Regularized nonlinear regression with dependent errors and its application to a biomechanical model

被引:0
|
作者
Hojun You
Kyubaek Yoon
Wei-Ying Wu
Jongeun Choi
Chae Young Lim
机构
[1] University of Houston,Department of Mathematics
[2] Yonsei University,The School of Mechanical Engineering
[3] National Dong Hwa University,Department of Applied Mathematics
[4] Seoul National University,Department of Statistics
来源
Annals of the Institute of Statistical Mathematics | 2024年 / 76卷
关键词
Nonlinear regression; Temporal dependence; Multiplicative error; Local consistency and oracle property;
D O I
暂无
中图分类号
学科分类号
摘要
A biomechanical model often requires parameter estimation and selection in a known but complicated nonlinear function. Motivated by observing that the data from a head-neck position tracking system, one of biomechanical models, show multiplicative time-dependent errors, we develop a modified penalized weighted least squares estimator. The proposed method can be also applied to a model with possible non-zero mean time-dependent additive errors. Asymptotic properties of the proposed estimator are investigated under mild conditions on a weight matrix and the error process. A simulation study demonstrates that the proposed estimation works well in both parameter estimation and selection with time-dependent error. The analysis and comparison with an existing method for head-neck position tracking data show better performance of the proposed method in terms of the variance accounted for.
引用
收藏
页码:481 / 510
页数:29
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