Maximum likelihood estimation of nonlinear mixed-effects models with crossed random effects by combining first-order conditional linearization and sequential quadratic programming

Liyong Fu; Mingliang Wang; Zuoheng Wang; Xinyu Song; Shouzheng Tang

首页> 外文期刊>生物数学学报：英文版 >Maximum likelihood estimation of nonlinear mixed-effects models with crossed random effects by combining first-order conditional linearization and sequential quadratic programming

【24h】

Maximum likelihood estimation of nonlinear mixed-effects models with crossed random effects by combining first-order conditional linearization and sequential quadratic programming

机译：结合一阶条件线性化和顺序二次规划的具有交叉随机效应的非线性混合效应模型的最大似然估计

获取原文

获取原文并翻译 | 示例

掌桥外文数据库（机构版） >>

开具论文收录证明 >>

页面导航

著录项
相关主题

机译：Nonlinear mixed-eirects (NLME) modek have become popular in various disciplines over the past several decades.However,the existing methods for parameter estimation imple-mented in standard statistical packages such as SAS and R/S-Plus are generally limited k) single-or multi-level NLME models that only allow nested random effects and are unable to cope with crossed random effects within the framework of NLME modeling.In t his study,wc propose a general formulation of NLME models that can accommodate both nested and crassed random effects,and then develop a computational algorit hm for parameter estimation based on normal assumptions.The maximum likelihood estimation is carried out using the first-order conditional expansion (FOCE) for NLME model linearization and sequential quadratic programming (SCJP) for computational optimization while ensuring positive-definiteness of the estimated variance-covariance matrices of both random effects and error terms.The FOCE-SQP algorithm is evaluated using the height and diameter data measured on trees from Korean larch (L.olgeiisis var,Chang-paienA.b) experimental plots aa well as simulation studies.We show that the FOCE-SQP method converges fast with high accuracy.Applications of the general formulation of NLME models are illustrated with an analysis of the Korean larch data.

著录项

来源
《生物数学学报：英文版》 |2019年第5期|P.1-18|共18页
作者
Liyong Fu; Mingliang Wang; Zuoheng Wang; Xinyu Song; Shouzheng Tang;
展开▼
作者单位

Research Institute of Forest Resource Information Techniques ChineJft Academy of Forestry Beijing 100091 P.R.China;

Center for Statistical Genetics Pennsylvania State University Loc T3436 Mailcode CH69 500 University Drive Hershey PA 17033 USA;

Wamell School of Forestry and Natural Resources University of Georgia Athens GA 30602 USA;

Department of Biostatistics Yale School of Public Healthy New Haven CT 06520 USA;

College of Computer and Information Techniques Xinyang Normal University Xinyang 464000 Henan Province P.R.China;

展开▼
收录信息
原文格式 PDF
正文语种 chi
中图分类文化、科学、教育、体育;
关键词
Crossed random effects; first-order conditional expansion; nested random effects; nonlinear mixed-effects models; sequential quadratic programming;

机译：交叉随机效应;一阶条件扩展;嵌套随机效应;非线性混合效应模型;顺序二次规划;

Maximum likelihood estimation of nonlinear mixed-effects models with crossed random effects by combining first-order conditional linearization and sequential quadratic programming

著录项

相关主题

期刊订阅