Abstract
Abstract. We consider robust methods of likelihood and frequentist inference for the nonlinear parameter, sayα, in conditionally linear nonlinear regression models. We derive closed‐form expressions for robust conditional, marginal, profile and modified profile likelihood functions forαunder elliptically contoured data distributions. Next, we develop robust exact‐F confidence intervals forαand 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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have