IMPROVED GAUSS-NEWTON ITERATION METHOD FOR NONLINEAR RANDOM EFFECT MODELS WITH RIGHT-CENSORED DATA

摘要：

This paper presents modified Gauss-Newton iteration algorithm for the nonlinear regression models with random effects for Failure Time Data set. The convergence of the iteration is proved carefully. Simulation illustrated that our method is available. Our results may be regarded as an extension of Wei (1998) for exponential nonlinear regression models without failure time data.

关键词： Gauss-Newton Iteration Method Right-Censored Data Nonlinear Random Effects Models

作者: ZONG Xu-ping FENG Guo-lin

作者单位: School of Mathematics, Yangzhou University Yangzhou, Jiangsu, 225002, China Chinese National Climate Center 100081, China

会议类型: 国际会议

会议名称: 第八届分布式计算及其应用国际学术研讨会(The 8th International Symposium on Distributed Computing and Applications to Business,Engineering and Science)

会议地点: 武汉

会议语种:英文

页码: 35-37

在线出版日期: 2009-10-16（万方平台首次上网日期，不代表论文的发表时间）