ABSTRACT

A useful model for data analysis is the partially nonlinear model where response variable is represented as the sum of a nonparametric and a parametric component. In this study, we propose a new procedure for estimating the parameters in the partially nonlinear models. Therefore, we consider penalized profile nonlinear least square problem where nonparametric components are expressed as a B-spline basis function, and then estimation problem is expressed in terms of conic quadratic programming which is a continuous optimization problem and solved interior point method. An application study is conducted to evaluate the performance of the proposed method by considering some well-known performance measures. The results are compared against parametric nonlinear model.

摘要

一个有用的数据分析模型是部分非线性模型，其中响应变量表示为非参数和参数分量的总和。在这项研究中，我们提出了一种新的方法来估计部分非线性模型中的参数。因此，我们考虑惩罚轮廓非线性最小二乘问题，其中非参数分量表示为B样条基函数，然后估计问题用连续优化问题和求解内点法的二次二次规划表示。通过考虑一些众所周知的性能度量，进行应用研究以评估所提出方法的性能。将结果与参数非线性模型进行比较。