Robust estimation of heteroscedastic regression models: a brief overview and new proposals
Year: 2025
Type: article
Abstract: We collect robust proposals given in the field of regression models with heteroscedastic errors. Our motivation stems from the fact that the practitioner frequently faces the confluence of two phenomena in the context of data analysis: nonlinearity and heteroscedasticity. The impact of heteroscedasticity on the precision of the estimators is well–known, however the conjunction of these two phenomena makes handling outliers more difficult. An iterative procedure to estimate the parameters of a heteroscedastic nonlinear model is considered. The studied estimators combine weighted $$MM-$$ M M - regression estimators, to control the impact of high leverage points, and a robust method to estimate the parameters of the variance function.
Source: Statistical Papers
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $2,890
Funders: Ministerio de Ciencia e Innovación, Universidad de Buenos Aires, Universidade de Lisboa, Ministerio de Asuntos Económicos y Transformación Digital, Gobierno de España, Fundação para a Ciência e a Tecnologia, Agencia Nacional de Promoción Científica y Tecnológica, Instituto Superior Técnico, Secretaria de Ciencia y Tecnica, Universidad de Buenos Aires, Agencia Estatal de Investigación, Fondo para la Investigación Científica y Tecnológica
OpenAlex ID: W4408746384