Abstract
In this article, we consider the application of the empirical likelihood method to a partially linear single-index model. We focus on the case where some covariates are measured with additive errors. It is shown that the empirical log-likelihood ratio at the true parameter converges to the standard chi-square distribution. Simulations show that the proposed confidence region has coverage probability which is closer to the nominal level, as well as narrower than those of normal approximation method. A real data example is given.
Mathematics Subject Classification:
Acknowledgment
This work was partially supported by the RFDP (No: 20020027010) and NSFC (No: 10771017).