Inference in the Symmetric Location Model: an Empirical Likelihood Approach
نویسندگان
چکیده
An empirical likelihood approach with an increasing number of estimated constraints is developed for inference in the symmetric location model. We obtain a Wilks’ Theorem for the resulting empirical likelihood and uniform local asymptotic normality. The former is used to obtain confidence regions and tests for the center of symmetry. The latter is used to show that the maximum empirical likelihood approach yields an asymptotically normal, semiparametrically efficient and adaptive estimator of the center of symmetry and to derive tests for symmetry.
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