The performance of a robust multistage estimator in nonlinear regression with heteroscedastic errors

In this article, a robust multistage parameter estimator is proposed for nonlinear regression with heteroscedastic variance, where the residual variances are considered as a general parametric function of predictors. The motivation is based on considering the chi-square distribution for the calculat...

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Main Authors: Riazoshams, Hossein, Midi, Habshah
Format: Article
Published: Taylor & Francis 2014
Online Access:http://psasir.upm.edu.my/id/eprint/35765/
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author Riazoshams, Hossein
Midi, Habshah
author_facet Riazoshams, Hossein
Midi, Habshah
author_sort Riazoshams, Hossein
building UPM Institutional Repository
collection Online Access
description In this article, a robust multistage parameter estimator is proposed for nonlinear regression with heteroscedastic variance, where the residual variances are considered as a general parametric function of predictors. The motivation is based on considering the chi-square distribution for the calculated sample variance of the data. It is shown that outliers that are influential in nonlinear regression parameter estimates are not necessarily influential in calculating the sample variance. This matter persuades us, not only to robustify the estimate of the parameters of the models for both the regression function and the variance, but also to replace the sample variance of the data by a robust scale estimate.
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institution Universiti Putra Malaysia
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spelling upm-357652016-02-10T03:18:54Z http://psasir.upm.edu.my/id/eprint/35765/ The performance of a robust multistage estimator in nonlinear regression with heteroscedastic errors Riazoshams, Hossein Midi, Habshah In this article, a robust multistage parameter estimator is proposed for nonlinear regression with heteroscedastic variance, where the residual variances are considered as a general parametric function of predictors. The motivation is based on considering the chi-square distribution for the calculated sample variance of the data. It is shown that outliers that are influential in nonlinear regression parameter estimates are not necessarily influential in calculating the sample variance. This matter persuades us, not only to robustify the estimate of the parameters of the models for both the regression function and the variance, but also to replace the sample variance of the data by a robust scale estimate. Taylor & Francis 2014 Article PeerReviewed Riazoshams, Hossein and Midi, Habshah (2014) The performance of a robust multistage estimator in nonlinear regression with heteroscedastic errors. Communications in Statistics - Simulation and Computation. pp. 1-28. ISSN 0361-0918; ESSN: 1532-4141 http://www.tandfonline.com/doi/abs/10.1080/03610918.2014.944657 10.1080/03610918.2014.944657
spellingShingle Riazoshams, Hossein
Midi, Habshah
The performance of a robust multistage estimator in nonlinear regression with heteroscedastic errors
title The performance of a robust multistage estimator in nonlinear regression with heteroscedastic errors
title_full The performance of a robust multistage estimator in nonlinear regression with heteroscedastic errors
title_fullStr The performance of a robust multistage estimator in nonlinear regression with heteroscedastic errors
title_full_unstemmed The performance of a robust multistage estimator in nonlinear regression with heteroscedastic errors
title_short The performance of a robust multistage estimator in nonlinear regression with heteroscedastic errors
title_sort performance of a robust multistage estimator in nonlinear regression with heteroscedastic errors
url http://psasir.upm.edu.my/id/eprint/35765/
http://psasir.upm.edu.my/id/eprint/35765/
http://psasir.upm.edu.my/id/eprint/35765/