nonlinear regression model

In nonlinear regression model, θ n is the least squares estimator for parameter θ, its consistency problem has a important background of statistic application, so its consistency problem has been studied by many statistic scientists, and has been resolved more perfectly.

在非线性回归模型中参数θ的最小二乘估计量θn的相合性问题有重要的统计应用背景，所以已经被许多统计学家研究过了，并已得到较完善的解决。

In aggregated data nonlinear regression model, a quasi score function is defined. Using projection likelihood and squared error and Fisher information, its optimality is proved.

本文定义了聚集数据非线性模型中的拟得分函数，从投影似然、均方误差和Fisher信息等方面证明了它的最优性。

Quasi Score Function in Aggregated Data Nonlinear Regression Model

聚集数据非线性模型中的拟得分函数

Then, nonlinear regression model is used to construct prediction interval for reliability parameters based on its point value derived from the trained neural network and the weights of network.

在网络训练得到的预测点值和网络权重的基础上，基于非线性回归模型构建可靠性参数的区间预测值。