Nonlinear regression models with profile nonlinear least squares estimation

2019 ◽  
pp. 1-18
Author(s):  
Jun Zhang ◽  
Yujie Gai
Keyword(s):  
Least Squares ◽  
Nonlinear Regression ◽  
Regression Models ◽  
Nonlinear Least Squares ◽  
Least Squares Estimation ◽  
Nonlinear Regression Models ◽  
Nonlinear Least Squares Estimation

LEAST SQUARES ESTIMATION FOR NONLINEAR REGRESSION MODELS WITH HETEROSCEDASTICITY

2021 ◽  
pp. 1-23
Author(s):  
Qiying Wang
Keyword(s):  
Least Squares ◽  
Nonlinear Regression ◽  
Regression Models ◽  
Asymptotic Theory ◽  
Nonlinear Least Squares ◽  
Least Squares Estimation ◽  
Nonlinear Regression Models ◽  
Nonlinear Least Squares Estimation ◽  
New Framework

This paper develops an asymptotic theory of nonlinear least squares estimation by establishing a new framework that can be easily applied to various nonlinear regression models with heteroscedasticity. As an illustration, we explore an application of the framework to nonlinear regression models with nonstationarity and heteroscedasticity. In addition to these main results, this paper provides a maximum inequality for a class of martingales, which is of interest in its own right.

scholarly journals A Monograph on Nonlinear Regression Models

2018 ◽  
Vol 7 (4.10) ◽  
pp. 543
Author(s):  
B. Mahaboob ◽  
B. Venkateswarlu ◽  
C. Narayana ◽  
J. Ravi sankar ◽  
P. Balasiddamuni
Keyword(s):  
Regression Model ◽  
Least Squares ◽  
Nonlinear Regression ◽  
Nonlinear Models ◽  
Nonlinear Least Squares ◽  
Error Variance ◽  
Ordinary Least Squares ◽  
Parameter Estimates ◽  
Nonlinear Regression Model ◽  
Nonlinear Regression Models

This research article uses Matrix Calculus techniques to study least squares application of nonlinear regression model, sampling distributions of nonlinear least squares estimators of regression parametric vector and error variance and testing of general nonlinear hypothesis on parameters of nonlinear regression model. Arthipova Irina et.al [1], in this paper, discussed some examples of different nonlinear models and the application of OLS (Ordinary Least Squares). MA Tabati et.al (2), proposed a robust alternative technique to OLS nonlinear regression method which provide accurate parameter estimates when outliers and/or influential observations are present. Xu Zheng et.al [3] presented new parametric tests for heteroscedasticity in nonlinear and nonparametric models.  

Optimal recursive iterative algorithm for discrete nonlinear least-squares estimation

1996 ◽  
Vol 19 (3) ◽  
pp. 643-649 ◽  
Author(s):  
Gordon T. Haupt ◽  
N. Jeremy Kasdin ◽  
George M. Keiser ◽  
Bradford W. Parkinson
Keyword(s):  
Least Squares ◽  
Iterative Algorithm ◽  
Nonlinear Least Squares ◽  
Least Squares Estimation ◽  
Nonlinear Least Squares Estimation
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