Abstract
This study investigates the empirical likelihood method for the partially linear additive models in which certain covariates are measured with additive errors. An empirical log-likelihood ratio for the parametric component is proposed based on the profile procedure, and a nonparametric version of the Wilk’s theorem is derived. Then, the confidence regions of the parametric component with asymptotically correct coverage probabilities are constructed by the obtained results. Furthermore, a simulation study is conducted to illustrate the performance of the proposed method.
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Wei, C., Luo, Y. & Wu, X. Empirical likelihood for partially linear additive errors-in-variables models. Stat Papers 53, 485–496 (2012). https://doi.org/10.1007/s00362-010-0354-1
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DOI: https://doi.org/10.1007/s00362-010-0354-1