Title

Robust Inference in Conditionally Linear Nonlinear Regression Model

Editor(s)

Rootzen, Holger and Rudemo, Mats

Abstract

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.

Department(s)

Mathematics and Statistics

Keywords and Phrases

calibration; conditionally linear regression models; elliptically contoured models; parallel line assay; pseudo-likelihoods; robust likelihoods; slope-ratio assays

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2008 Wiley-Blackwell, All rights reserved.

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