Empirical likelihood inference for error density estimators in first-order autoregression models

Hui Zhou and Jie Li

Communications in Statistics - Theory and Methods, 2018, vol. 47, issue 10, 2351-2361

Abstract: In this paper we apply empirical likelihood method to the error density estimators in first-order autoregressive models under some mild conditions. The log-likelihood ratio statistic is shown to be asymptotically chi-squared distributed at a fixed point. In simulation, we show that the empirical likelihood produces confidence intervals having theoretical coverage accuracy which is better than normal approximation.

Date: 2018
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DOI: 10.1080/03610926.2014.974820

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