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>Empirical likelihood based diagnostics for heteroscedasticity in partial linear models
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Empirical likelihood based diagnostics for heteroscedasticity in partial linear models
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机译:部分线性模型中基于经验似然性的异方差诊断
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摘要
In this paper, we propose a diagnostic technique for checking heteroscedasticity based on empirical likelihood for the partial linear models. We construct an empirical likelihood ratio test for heteroscedasticity. Also, under mild conditions, a nonparametric version of Wilk's theorem is derived, which says that our proposed test has an asymptotic chi-square distribution. Simulation results reveal that the finite sample performance of our proposed test is satisfactory in both size and power. An empirical likelihood bootstrap simulation is also conducted to overcome the size distortion in small sample sizes.
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