Empirical likelihood for heteroscedastic partially linear errors-in-variables model with α-mixing errors

Guo-Liang Fan (), Han-Ying Liang and Jiang-Feng Wang

Statistical Papers, 2013, vol. 54, issue 1, 85-112

Abstract: In this paper, we apply the empirical likelihood method to heteroscedastic partially linear errors-in-variables model. For the cases of known and unknown error variances, the two different empirical log-likelihood ratios for the parameter of interest are constructed. If the error variances are known, the empirical log-likelihood ratio is proved to be asymptotic chi-square distribution under the assumption that the errors are given by a sequence of stationary α-mixing random variables. Furthermore, if the error variances are unknown, we show that the proposed statistic is asymptotically standard chi-square distribution when the errors are independent. Simulations are carried out to assess the performance of the proposed method. Copyright Springer-Verlag 2013

Keywords: Empirical likelihood; Partially linear errors-in-variables model; Heteroscedastic; α-Mixing; Confidence region; 62G15; 62E20 (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s00362-011-0412-3

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