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• W2158080109 abstract "The paper considers testing parametric assumptions on the conditional mean and variance functions for nonlinear autoregressive models. To this end, we compare the kernel density estimate of the marginal density of the process with a convolution-type density estimate. It is shown that, interestingly, the latter estimate has a parametric $left( {sqrt n } right)$ rate of convergence, thus substantially improving the classical kernel density estimates whose rates of convergence are much inferior. Our results are confirmed by a simulation study for threshold autoregressive processes and autoregressive conditional heteroskedastic processes." @default.
• W2158080109 created "2016-06-24" @default.
• W2158080109 creator A5003318881 @default.
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• W2158080109 date "2014-10-02" @default.
• W2158080109 modified "2023-09-27" @default.
• W2158080109 title "PARAMETRIC SPECIFICATION TEST FOR NONLINEAR AUTOREGRESSIVE MODELS" @default.
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• W2158080109 doi "https://doi.org/10.1017/s0266466614000681" @default.
• W2158080109 hasPublicationYear "2014" @default.
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