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An ANOVA-type nonparametric diagnostic test for heteroscedastic regression models

机译:异方差回归模型的ANOVA型非参数诊断检验

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For the heteroscedastic nonparametric regression model Y_(ni) = m(_(ni)) + σ (x_(ni))∈_(ni), i = 1.....n, we discuss a novel method for testing some parametric assumptions about the regression function m. The test is motivated by recent developments in the asymptotic theory for analysis of variance when the number of factor levels is large. Asymptotic normality of the test statistic is established under the null hypothesis and suitable local alternatives. The similarity of the form of the test statistic to that of the classical F-statistic in analysis of variance allows easy and fast calculation. Simulation studies demonstrate that the new test possesses satisfactory finite-sample properties.
机译:对于异方差非参数回归模型Y_(ni)= m(_(ni))+σ(x_(ni))∈_(ni),i = 1 ..... n,我们讨论了一种新颖的方法来测试关于回归函数的参数假设。当因子水平的数量很大时,该检验受到渐近理论最新发展的推动,该理论用于分析方差。检验统计量的渐近正态性是在原假设和合适的局部替代条件下建立的。在方差分析中,检验统计量的形式与经典F统计量的形式相似,可以轻松快速地进行计算。仿真研究表明,该新测试具有令人满意的有限样本属性。

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