Empirical likelihood-based dimension reduction inference for linear error-in-responses models with validation study |
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Authors: | Email author" target="_blank">Qihua?WangEmail author H?rdie?Wolfgang |
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Institution: | 1. Academy of Mathematics and System Sciences, Chinese Academy of Sciences, Beijing 100080, China;Heilongjiang University, Harbin 150080, China 2. Center for Applied Statistics and Economics, Humboldt-Universit(a)t zu Berlin, 10178 Berlin, Germany |
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Abstract: | In this paper, linear errors-in-response models are considered in the presence of validation data on the responses. A semiparametric
dimension reduction technique is employed to define an estimator of β with asymptotic normality, the estimated empirical loglikelihoods
and the adjusted empirical loglikelihoods for the vector of regression coefficients and linear combinations of the regression
coefficients, respectively. The estimated empirical log-likelihoods are shown to be asymptotically distributed as weighted
sums of independent X
2
1 and the adjusted empirical loglikelihoods are proved to be asymptotically distributed as standard chi-squares, respectively. |
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Keywords: | confidence intervals error-in-response validation data |
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