Asymptotics of least-squares estimators for constrained nonlinear regression
成果类型：
Article
署名作者：
Wang, JD
刊物名称：
ANNALS OF STATISTICS
ISSN/ISSBN：
0090-5364
发表日期：
1996
页码：
1316-1326
关键词：
摘要：
This paper is devoted do studying the asymptotic behavior of LS-estimators in constrained nonlinear regression problems. Here the constraints are given by nonlinear equalities and inequalities. Thus this is a very general setting. Essentially this kind of estimation problem is a stochastic optimization problem. So we make use of methods in optimization to overcome the difficulty caused by nonlinearity in the regression model and given constraints.