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Locally asymptotically powerful test for nonlinear autoregressive models

机译:非线性自回归模型的局部渐近有效检验

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摘要

We propose a locally asymptotically powerful test to simultaneously examine hypotheses relative to the parametric form of the conditional mean and the conditional variance functions in a class of nonlinear semi-parametric time series models without a specified error law. On the basis of a modified version of the Le Cam method of Hwang and Basawa (2001), we establish the local asymptotic normality relative to the model. The main result shows that the test statistic built by substituting consistent estimated residuals and parameters for the theoretical ones is asymptotically normal. Its asymptotic power is computed and the result is illustrated by some simulations.
机译:我们提出了一种局部渐近有效检验,以同时检验一类非线性半参数时间序列模型中没有指定误差定律的相对于条件均值和条件方差函数的参数形式的假设。在Hwang和Basawa(2001)的Le Cam方法的修改版本的基础上,我们建立了相对于模型的局部渐近正态性。主要结果表明,通过将一致的估计残差和参数替换为理论残差和参数而建立的检验统计量是渐近正态的。计算其渐近幂,并通过一些仿真来说明结果。

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