Instrumental variable-based empirical likelihood inferences for varying-coefficient models with error-prone covariates |
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Authors: | Peixin Zhao Liugen Xue |
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Institution: | 1. Department of Mathematics , Hechi University , Yizhou , Guangxi , 546300 , People's Republic of China;2. College of Applied Sciences , Beijing University of Technology , Beijing , 100124 , People's Republic of China |
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Abstract: | This paper presents the empirical likelihood inferences for a class of varying-coefficient models with error-prone covariates. We focus on the case that the covariance matrix of the measurement errors is unknown and neither repeated measurements nor validation data are available. We propose an instrumental variable-based empirical likelihood inference method and show that the proposed empirical log-likelihood ratio is asymptotically chi-squared. Then, the confidence intervals for the varying-coefficient functions are constructed. Some simulation studies and a real data application are used to assess the finite sample performance of the proposed empirical likelihood procedure. |
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Keywords: | varying-coefficient models error-prone covariate empirical likelihood instrumental variable confidence intervals |
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