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| The empirical likelihood goodness-of-fit test for regression model | |
| 作者单位： | Li-xing ZHU（Department of Mathematics, Hong Kong Baptist University, Kowloon Tong, Hong Kong, China） ; Yong-song QIN（School of Mathematical Sciences, Guangxi Normal Uinversity, Guilin 541004, China） ; Wang-li XU（School of Statistics, Renmin University of China, Beijing 100875, China） ; |
| 摘 要： | Goodness-of-fit test for regression modes has received much attention in literature. In this paper, empirical likelihood (EL) goodness-of-fit tests for regression models including classical parametric and autoregressive (AR) time series models are proposed. Unlike the existing locally smoothing and globally smoothing methodologies, the new method has the advantage that the tests are self-scale invariant and that the asymptotic null distribution is chi-squared. Simulations are carried out to illustrate the methodology. |
The empirical likelihood goodness-of-fit test for regression model |
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| Authors: | Li-xing Zhu Yong-song Qin Wang-li Xu |
| Institution: | 1. Department of Mathematics, Hong Kong Baptist University, Kowloon Tong, Hong Kong, China 2. School of Mathematical Sciences, Guangxi Normal Uinversity, Guilin 541004, China 3. School of Statistics, Renmin University of China, Beijing 100875, China |
| Abstract: | Goodness-of-fit test for regression modes has received much attention in literature. In this paper, empirical likelihood (EL) goodness-of-fit tests for regression models including classical parametric and autoregressive (AR) time series models are proposed. Unlike the existing locally smoothing and globally smoothing methodologies, the new method has the advantage that the tests are self-scale invariant and that the asymptotic null distribution is chi-squared. Simulations are carried out to illustrate the methodology. |
| Keywords: | regression model AR time series models empirical likelihood asymptotic normality goodness-of-fit |
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