非线性回归模型估计的数值技术

Dr Ranadheer Donthi
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引用次数: 12

摘要

近五十年来,关于非线性回归模型数值拟合的文献有了很大的发展。非线性回归问题的一个重要阶段是探究自变量和因变量之间的关系。非线性回归模型的一个很大程度上未开发的研究领域涉及非线性参数的有限样本性质。本研究的主要目的是提出一些非线性回归模型的非线性估计方法,即Newton-Raphson法、Gauss-Newton法、记分法、二次爬坡法和共轭梯度法。2005年,G.E. Hovland等人(见[5])。在他的研究中,提出了一种联合循环电厂模型物理时变参数的参数估计方法。B. Mahaboob等人(见[6])在研究论文中提出了一些基于数值分析的非线性回归模型参数估计的计算方法。S.J. Juliear等人(参见[7])在其研究论文中开发了unscented变换(UT)方法,通过非线性变换传播均值和协方差信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Numerical Techniques of Nonlinear Regression Model Estimation
The literature on numerical methods for fitting nonlinear regression model has grown enormously in the fast five decades. An important phase in nonlinear regression problems is the exploration of the relation between the independent and dependent variables. A largely unexplored area of research in nonlinear regression models concerns the finite sample properties of nonlinear parameters. The main object of this research study is to propose some nonlinear methods of estimation of nonlinear regression models, namely Newton-Raphson method, Gauss-Newton method, Method of scoring, Quadratic Hill-Climbing and Conjugate Gradient methods. In 2005, G.E. Hovland et al (see [5]). In his research article, presented a parameter estimation of physical time-varying parameters for combined-cycle power plant models. B. Mahaboob et al. (see [6]), in their research paper, proposed some computational methods based on numerical analysis to estimate the parameters of nonlinear regression model. S.J. Juliear et al. (see [7]), in their research paper, developed the method of unscented transformation (UT) to propagate mean and covariance information through nonlinear transformations.
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