Empirical likelihood for density-weighted average derivatives |
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Authors: | Wanrong Liu Xuewen Lu |
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Institution: | (1) Department of Applied Mathematics, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059 Cracow, Poland |
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Abstract: | In this paper, we investigate empirical likelihood (EL) inference for density-weighted average derivatives in nonparametric
multiple regression models. A simply adjusted empirical log-likelihood ratio for the vector of density-weighted average derivatives
is defined and its limiting distribution is shown to be a standard Chi-square distribution. To increase the accuracy and coverage
probability of confidence regions, an EL inference procedure for the rescaled parameter vector is proposed by using a linear
instrumental variables regression. The new method shares the same properties of the regular EL method with i.i.d. samples.
For example, estimation of limiting variances and covariances is not needed. A Monte Carlo simulation study is presented to
compare the new method with the normal approximation method and an existing EL method. |
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Keywords: | |
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