Robust Inference in Conditionally Linear Nonlinear Regression Model
Rootzen, Holger and Rudemo, Mats
We consider robust methods of likelihood and frequentist inference for the nonlinear parameter, say α, in conditionally linear nonlinear regression models. We derive closed-form expressions for robust conditional, marginal, profile and modified profile likelihood functions for α under elliptically contoured data distributions. Next, we develop robust exact-F confidence intervals for α and consider robust Fieller intervals for ratios of regression parameters in linear models. Several well-known examples are considered and Monte Carlo simulation results are presented.
R. Paige and P. H. Fernando, "Robust Inference in Conditionally Linear Nonlinear Regression Model," Scandinavian Journal of Statistics, Wiley-Blackwell, Jan 2008.
The definitive version is available at https://doi.org/10.1111/j.1467-9469.2007.00570.x
Mathematics and Statistics
Keywords and Phrases
calibration; conditionally linear regression models; elliptically contoured models; parallel line assay; pseudo-likelihoods; robust likelihoods; slope-ratio assays
International Standard Serial Number (ISSN)
Article - Journal
© 2008 Wiley-Blackwell, All rights reserved.
01 Jan 2008