Asymptotics of least-squares estimators for constrained nonlinear regression
约束非线性回归中最小二乘估计量的渐近性质
This paper is devoted to 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.