Improved maximum likelihood estimators in a heteroskedastic errors-in-variables model

• Published in: arXiv.org
• Main Authors: Patriota, Alexandre G, Lemonte, Artur J, Bolfarine, Heleno
• Format: Paper Journal Article
• Language: English
• Published: Ithaca Cornell University Library, arXiv.org 26.08.2015
• Subjects: Analytical chemistry; Astrophysics; Bias; Computer simulation; Economic models; Epidemiology; Mathematical models; Maximum likelihood estimators; Monte Carlo simulation; Organic chemistry; Statistics - Methodology
• ISSN: 2331-8422
• DOI: 10.48550/arxiv.0903.3146

This paper develops a bias correction scheme for a multivariate heteroskedastic errors-in-variables model. The applicability of this model is justified in areas such as astrophysics, epidemiology and analytical chemistry, where the variables are subject to measurement errors and the variances vary with the observations. We conduct Monte Carlo simulations to investigate the performance of the corrected estimators. The numerical results show that the bias correction scheme yields nearly unbiased estimates. We also give an application to a real data set.